[{"oa":"1","citation":{"apa":"Itner, D., Dreiling, D., Gravenkamp, H., Henning, B., & Birk, C. (2026). A modified Levenberg–Marquardt method for estimating the elastic material parameters of polymer waveguides using residuals between autocorrelated frequency responses. Mechanical Systems and Signal Processing, 247, 113904. https://doi.org/10.1016/j.ymssp.2026.113904","ieee":"D. Itner, D. Dreiling, H. Gravenkamp, B. Henning, and C. Birk, “A modified Levenberg–Marquardt method for estimating the elastic material parameters of polymer waveguides using residuals between autocorrelated frequency responses,” Mechanical Systems and Signal Processing, vol. 247, p. 113904, 2026, doi: https://doi.org/10.1016/j.ymssp.2026.113904.","short":"D. Itner, D. Dreiling, H. Gravenkamp, B. Henning, C. Birk, Mechanical Systems and Signal Processing 247 (2026) 113904.","chicago":"Itner, Dominik, Dmitrij Dreiling, Hauke Gravenkamp, Bernd Henning, and Carolin Birk. “A Modified Levenberg–Marquardt Method for Estimating the Elastic Material Parameters of Polymer Waveguides Using Residuals between Autocorrelated Frequency Responses.” Mechanical Systems and Signal Processing 247 (2026): 113904. https://doi.org/10.1016/j.ymssp.2026.113904.","mla":"Itner, Dominik, et al. “A Modified Levenberg–Marquardt Method for Estimating the Elastic Material Parameters of Polymer Waveguides Using Residuals between Autocorrelated Frequency Responses.” Mechanical Systems and Signal Processing, vol. 247, 2026, p. 113904, doi:https://doi.org/10.1016/j.ymssp.2026.113904.","ama":"Itner D, Dreiling D, Gravenkamp H, Henning B, Birk C. A modified Levenberg–Marquardt method for estimating the elastic material parameters of polymer waveguides using residuals between autocorrelated frequency responses. Mechanical Systems and Signal Processing. 2026;247:113904. doi:https://doi.org/10.1016/j.ymssp.2026.113904","bibtex":"@article{Itner_Dreiling_Gravenkamp_Henning_Birk_2026, title={A modified Levenberg–Marquardt method for estimating the elastic material parameters of polymer waveguides using residuals between autocorrelated frequency responses}, volume={247}, DOI={https://doi.org/10.1016/j.ymssp.2026.113904}, journal={Mechanical Systems and Signal Processing}, author={Itner, Dominik and Dreiling, Dmitrij and Gravenkamp, Hauke and Henning, Bernd and Birk, Carolin}, year={2026}, pages={113904} }"},"project":[{"_id":"89","name":"Vollständige Bestimmung der akustischen Materialparameter von Polymeren"}],"_id":"63800","page":"113904","volume":247,"user_id":"32616","status":"public","date_created":"2026-01-29T08:53:42Z","department":[{"_id":"49"}],"type":"journal_article","keyword":["Material parameter estimation","Waveguide","Nonlinear optimization","Inverse problem","Least squares"],"publication":"Mechanical Systems and Signal Processing","abstract":[{"lang":"eng","text":"In this contribution, we address the estimation of the frequency-dependent elastic parameters of polymers in the ultrasound range, which is formulated as an inverse problem. This inverse problem is implemented as a nonlinear regression-type optimization problem, in which the simulation signals are fitted to the measurement signals. These signals consist of displacement responses in waveguides, focusing on hollow cylindrical geometries to enhance the simulation efficiency. To accelerate the optimization and reduce the number of model evaluations and wait times, we propose two novel methods. First, we introduce an adaptation of the Levenberg–Marquardt method derived from a geometrical interpretation of the least-squares optimization problem. Second, we introduce an improved objective function based on the autocorrelated envelopes of the measurement and simulation signals. Given that this study primarily relies on simulation data to quantify optimization convergence, we aggregate the expected ranges of realistic material parameters and derive their distributions to ensure the reproducibility of optimizations with proper measurements. We demonstrate the effectiveness of our objective function modification and step adaptation for various materials with isotropic material symmetry by comparing them with the Broyden–Fletcher–Goldfarb–Shanno method. In all cases, our method reduces the total number of model evaluations, thereby shortening the time to identify the material parameters."}],"language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://www.sciencedirect.com/science/article/pii/S0888327026000610/pdfft?md5=16e8493b44527f4ab0a6d13f634a01c3&pid=1-s2.0-S0888327026000610-main.pdf"}],"doi":"https://doi.org/10.1016/j.ymssp.2026.113904","publication_identifier":{"issn":["0888-3270"]},"author":[{"full_name":"Itner, Dominik","first_name":"Dominik","last_name":"Itner"},{"full_name":"Dreiling, Dmitrij","last_name":"Dreiling","first_name":"Dmitrij","id":"32616"},{"full_name":"Gravenkamp, Hauke","last_name":"Gravenkamp","first_name":"Hauke"},{"full_name":"Henning, Bernd","last_name":"Henning","first_name":"Bernd","id":"213"},{"last_name":"Birk","first_name":"Carolin","full_name":"Birk, Carolin"}],"year":"2026","title":"A modified Levenberg–Marquardt method for estimating the elastic material parameters of polymer waveguides using residuals between autocorrelated frequency responses","intvolume":" 247","date_updated":"2026-02-02T12:44:47Z","publication_status":"published"},{"project":[{"_id":"124","name":"TRR 318 - C1: TRR 318 - Subproject C1 - Gesundes Misstrauen in Erklärungen"}],"citation":{"short":"T.M. Peters, I. Scharlau, Frontiers in Psychology 16 (2025).","chicago":"Peters, Tobias Martin, and Ingrid Scharlau. “Interacting with Fallible AI: Is Distrust Helpful When Receiving AI Misclassifications?” Frontiers in Psychology 16 (2025). https://doi.org/10.3389/fpsyg.2025.1574809.","apa":"Peters, T. M., & Scharlau, I. (2025). Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications? Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1574809","ieee":"T. M. Peters and I. Scharlau, “Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications?,” Frontiers in Psychology, vol. 16, 2025, doi: 10.3389/fpsyg.2025.1574809.","ama":"Peters TM, Scharlau I. Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications? Frontiers in Psychology. 2025;16. doi:10.3389/fpsyg.2025.1574809","bibtex":"@article{Peters_Scharlau_2025, title={Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications?}, volume={16}, DOI={10.3389/fpsyg.2025.1574809}, journal={Frontiers in Psychology}, author={Peters, Tobias Martin and Scharlau, Ingrid}, year={2025} }","mla":"Peters, Tobias Martin, and Ingrid Scharlau. “Interacting with Fallible AI: Is Distrust Helpful When Receiving AI Misclassifications?” Frontiers in Psychology, vol. 16, 2025, doi:10.3389/fpsyg.2025.1574809."},"status":"public","volume":16,"user_id":"92810","_id":"59755","abstract":[{"lang":"eng","text":"Due to the application of Artificial Intelligence (AI) in high-risk domains like law or medicine,\r\ntrustworthy AI and trust in AI are of increasing scientific and public relevance. A typical conception,\r\nfor example in the context of medical diagnosis, is that a knowledgeable user receives AIgenerated\r\nclassification as advice. Research to improve such interactions often aims to foster the\r\nuser’s trust, which in turn should improve the combined human-AI performance. Given that AI\r\nmodels can err, we argue that the possibility to critically review, thus to distrust, an AI decision is\r\nan equally interesting target of research.\r\nWe created two image classification scenarios in which the participants received mock-up\r\nAI advice. The quality of the advice decreases for a phase of the experiment. We studied the\r\ntask performance, trust and distrust of the participants, and tested whether an instruction to\r\nremain skeptical and review each piece of advice led to a better performance compared to a\r\nneutral condition. Our results indicate that this instruction does not improve but rather worsens\r\nthe participants’ performance. Repeated single-item self-report of trust and distrust shows an\r\nincrease in trust and a decrease in distrust after the drop in the AI’s classification quality, with no\r\ndifference between the two instructions. Furthermore, via a Bayesian Signal Detection Theory\r\nanalysis, we provide a procedure to assess appropriate reliance in detail, by quantifying whether\r\nthe problems of under- and over-reliance have been mitigated. We discuss implications of our\r\nresults for the usage of disclaimers before interacting with AI, as prominently used in current\r\nLLM-based chatbots, and for trust and distrust research."}],"publication":"Frontiers in Psychology","department":[{"_id":"424"},{"_id":"660"}],"type":"journal_article","keyword":["trust in AI","trust","distrust","human-AI interaction","Signal Detection Theory","Bayesian parameter estimation","image classification"],"date_created":"2025-05-02T09:22:39Z","article_type":"original","intvolume":" 16","publication_status":"published","date_updated":"2025-05-27T09:10:09Z","author":[{"id":"92810","full_name":"Peters, Tobias Martin","first_name":"Tobias Martin","orcid":"0009-0008-5193-6243","last_name":"Peters"},{"id":"451","full_name":"Scharlau, Ingrid","first_name":"Ingrid","orcid":"0000-0003-2364-9489","last_name":"Scharlau"}],"title":"Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications?","year":"2025","doi":"10.3389/fpsyg.2025.1574809","language":[{"iso":"eng"}]},{"page":"3326-3335","_id":"63498","user_id":"83383","doi":"10.1109/TPEL.2024.3488174","volume":40,"year":"2025","status":"public","title":"HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores","author":[{"full_name":"Kirchgässner, Wilhelm","first_name":"Wilhelm","last_name":"Kirchgässner"},{"first_name":"Nikolas","last_name":"Förster","full_name":"Förster, Nikolas"},{"first_name":"Till","last_name":"Piepenbrock","full_name":"Piepenbrock, Till"},{"last_name":"Schweins","first_name":"Oliver","full_name":"Schweins, Oliver"},{"full_name":"Wallscheid, Oliver","first_name":"Oliver","last_name":"Wallscheid"}],"date_updated":"2026-01-06T08:08:01Z","intvolume":" 40","date_created":"2026-01-06T08:07:13Z","keyword":["Mathematical models","Estimation","Data models","Convolutional neural networks","Accuracy","Magnetic hysteresis","Magnetic cores","Temperature measurement","Magnetic domains","Temperature distribution","Convolutional neural network (CNN)","machine learning (ML)","magnetics"],"type":"journal_article","department":[{"_id":"52"}],"publication":"IEEE Transactions on Power Electronics","issue":"2","citation":{"mla":"Kirchgässner, Wilhelm, et al. “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores.” IEEE Transactions on Power Electronics, vol. 40, no. 2, 2025, pp. 3326–35, doi:10.1109/TPEL.2024.3488174.","ama":"Kirchgässner W, Förster N, Piepenbrock T, Schweins O, Wallscheid O. HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores. IEEE Transactions on Power Electronics. 2025;40(2):3326-3335. doi:10.1109/TPEL.2024.3488174","bibtex":"@article{Kirchgässner_Förster_Piepenbrock_Schweins_Wallscheid_2025, title={HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores}, volume={40}, DOI={10.1109/TPEL.2024.3488174}, number={2}, journal={IEEE Transactions on Power Electronics}, author={Kirchgässner, Wilhelm and Förster, Nikolas and Piepenbrock, Till and Schweins, Oliver and Wallscheid, Oliver}, year={2025}, pages={3326–3335} }","apa":"Kirchgässner, W., Förster, N., Piepenbrock, T., Schweins, O., & Wallscheid, O. (2025). HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores. IEEE Transactions on Power Electronics, 40(2), 3326–3335. https://doi.org/10.1109/TPEL.2024.3488174","ieee":"W. Kirchgässner, N. Förster, T. Piepenbrock, O. Schweins, and O. Wallscheid, “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores,” IEEE Transactions on Power Electronics, vol. 40, no. 2, pp. 3326–3335, 2025, doi: 10.1109/TPEL.2024.3488174.","short":"W. Kirchgässner, N. Förster, T. Piepenbrock, O. Schweins, O. Wallscheid, IEEE Transactions on Power Electronics 40 (2025) 3326–3335.","chicago":"Kirchgässner, Wilhelm, Nikolas Förster, Till Piepenbrock, Oliver Schweins, and Oliver Wallscheid. “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores.” IEEE Transactions on Power Electronics 40, no. 2 (2025): 3326–35. https://doi.org/10.1109/TPEL.2024.3488174."}},{"user_id":"43992","volume":423,"_id":"56940","status":"public","supervisor":[{"id":"15402","last_name":"Timmermann","first_name":"Julia","full_name":"Timmermann, Julia"},{"full_name":"Mikut, Ralf","last_name":"Mikut","first_name":"Ralf"}],"citation":{"mla":"Götte, Ricarda-Samantha. Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit. 2024, doi:10.17619/UNIPB/1-2066.","ama":"Götte R-S. Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit. Vol 423.; 2024. doi:10.17619/UNIPB/1-2066","bibtex":"@book{Götte_2024, series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit}, volume={423}, DOI={10.17619/UNIPB/1-2066}, author={Götte, Ricarda-Samantha}, year={2024}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts} }","apa":"Götte, R.-S. (2024). Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit (Vol. 423). https://doi.org/10.17619/UNIPB/1-2066","ieee":"R.-S. Götte, Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit, vol. 423. 2024.","chicago":"Götte, Ricarda-Samantha. Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit. Vol. 423. Verlagsschriftenreihe des Heinz Nixdorf Instituts, 2024. https://doi.org/10.17619/UNIPB/1-2066.","short":"R.-S. Götte, Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit, 2024."},"doi":"10.17619/UNIPB/1-2066","series_title":"Verlagsschriftenreihe des Heinz Nixdorf Instituts","language":[{"iso":"ger"}],"date_updated":"2024-11-07T11:47:59Z","publication_status":"published","intvolume":" 423","title":"Online-Schätzung von Modellungenauigkeiten zur automatischen Modelladaption unter Beibehaltung einer physikalisch-technischen Interpretierbarkeit","year":"2024","publication_identifier":{"isbn":["978-3-947647-42-2"]},"author":[{"full_name":"Götte, Ricarda-Samantha","last_name":"Götte","first_name":"Ricarda-Samantha","id":"43992"}],"type":"dissertation","keyword":["state estimation","joint estimation","sparsity"],"department":[{"_id":"880"},{"_id":"153"}],"date_created":"2024-11-07T11:43:05Z","abstract":[{"lang":"ger","text":"Ziel dieser Arbeit ist die Entwicklung eines modellbasierten Beobachters für eingangsaffine, nichtlineare Systeme, der trotz Modellungenauigkeiten eine hohe Schätzgüte erzielt und zusätzlich eine parametrische, physikalisch interpretierbare Darstellung dieser ermöglicht. Diese soll zur automatisierten Verbesserung des Modells verwendet werden. Die vorliegende Arbeit analysiert sowohl Techniken der hybriden Systemidentifikation wie physikalisch motivierte neuronale Netze, als auch Methoden zur Kompensation von Modellungenauigkeiten im Beobachterentwurf. Basierend auf der Analyse wird ein neuartiger, modellbasierter Beobachter entworfen, der Systemzustände und Modellungenauigkeiten gleichzeitig schätzt und insbesondere eine parametrische, physikalisch interpretierbare Darstellung der Ungenauigkeiten erzielt. Diese besteht aus einer Linearkombination von physikalisch interpretierbaren Funktionen, deren dazugehörige, dünnbesetzt modellierte Parameter mithilfe eines augmentierten Zustands parallel zu den Systemzuständen geschätzt werden. Das Novum dieser Arbeit stellt somit die echtzeitfähige Schätzung von Zuständen und Modellungenauigkeiten in physikalisch-technischer Form dar, auf deren Grundlage ein Konzept zur automatisierten Modelladaption umgesetzt wird. Die Applikation der neuartigen Methode ist in der Situation auftretender Systemveränderungen besonders vorteilhaft, da diese zur Laufzeit durch den augmentierten Beobachter\r\ngeschätzt und identifiziert werden können. "},{"text":"The aim of this thesis is the development of a model-based observer for input-affine, nonlinear systems that achieves a high estimation quality despite model inaccuracies. By additionally providing a parametric, physically interpretable representation of the model inaccuracies, an automated improvement of the model should be enabled. This thesis\r\nanalyzes techniques of hybrid system identification such as physics-guided neural networks, as well as methods for compensating model inaccuracies within the observer design. Based on this analysis, a novel model-based observer is designed, which estimates states and model inaccuracies jointly and, in particular, obtains a parametric, physically\r\ninterpretable representation of the inaccuracies. This consists of a linear combination of physically interpretable functions, whose associated parameters are modeled sparse and estimated in parallel to the system’s states using an augmented state. The novelty of this thesis is thus the real-time capability to jointly estimate states and model inaccuracies in a physical-technical manner, on the basis of which an automated model adaption can be\r\ncarried out. The application of the new methodology is particularly advantageous in the situation of occurring system changes since these can be estimated and identified at run time by the augmented observer.","lang":"eng"}]},{"quality_controlled":"1","citation":{"chicago":"Götte, Ricarda-Samantha, and Julia Timmermann. “Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF.” In 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), 56:85–90, 2023. https://doi.org/10.1016/j.ifacol.2023.02.015.","short":"R.-S. Götte, J. Timmermann, in: 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), 2023, pp. 85–90.","apa":"Götte, R.-S., & Timmermann, J. (2023). Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF. 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), 56(1), 85–90. https://doi.org/10.1016/j.ifacol.2023.02.015","ieee":"R.-S. Götte and J. Timmermann, “Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF,” in 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), Canberra, Australien, 2023, vol. 56, no. 1, pp. 85–90, doi: https://doi.org/10.1016/j.ifacol.2023.02.015.","ama":"Götte R-S, Timmermann J. Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF. In: 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022). Vol 56. ; 2023:85-90. doi:https://doi.org/10.1016/j.ifacol.2023.02.015","bibtex":"@inproceedings{Götte_Timmermann_2023, title={Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF}, volume={56}, DOI={https://doi.org/10.1016/j.ifacol.2023.02.015}, number={1}, booktitle={12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)}, author={Götte, Ricarda-Samantha and Timmermann, Julia}, year={2023}, pages={85–90} }","mla":"Götte, Ricarda-Samantha, and Julia Timmermann. “Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF.” 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), vol. 56, no. 1, 2023, pp. 85–90, doi:https://doi.org/10.1016/j.ifacol.2023.02.015."},"volume":56,"user_id":"43992","_id":"34171","page":"85-90","conference":{"location":"Canberra, Australien","start_date":"2023-01-04","name":"12th IFAC Symposium on Nonlinear Control Systems NOLCOS 2022","end_date":"2023-01-06"},"status":"public","department":[{"_id":"153"},{"_id":"880"}],"type":"conference","keyword":["joint estimation","unscented transform","Kalman filter","sparsity","data-driven","compressed sensing"],"date_created":"2022-12-01T07:17:00Z","abstract":[{"text":"State estimation when only a partial model of a considered system is available remains a major challenge in many engineering fields. This work proposes a joint, square-root unscented Kalman filter to estimate states and model uncertainties simultaneously by linear combinations of physics-motivated library functions. Using a sparsity promoting approach, a selection of those linear combinations is chosen and thus an interpretable model can be extracted. Results indicate a small estimation error compared to a traditional square-root unscented Kalman filter and exhibit the enhancement of physically meaningful models.","lang":"eng"}],"issue":"1","publication":"12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)","doi":"https://doi.org/10.1016/j.ifacol.2023.02.015","language":[{"iso":"eng"}],"intvolume":" 56","date_updated":"2024-11-13T08:43:05Z","author":[{"full_name":"Götte, Ricarda-Samantha","last_name":"Götte","first_name":"Ricarda-Samantha","id":"43992"},{"first_name":"Julia","last_name":"Timmermann","full_name":"Timmermann, Julia","id":"15402"}],"year":"2023","title":"Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF"},{"abstract":[{"lang":"eng","text":"Low-quality models that miss relevant dynamics lead to major challenges in modelbased\r\nstate estimation. We address this issue by simultaneously estimating the system’s states\r\nand its model inaccuracies by a square root unscented Kalman filter (SRUKF). Concretely,\r\nwe augment the state with the parameter vector of a linear combination containing suitable\r\nfunctions that approximate the lacking dynamics. Presuming that only a few dynamical terms\r\nare relevant, the parameter vector is claimed to be sparse. In Bayesian setting, properties like\r\nsparsity are expressed by a prior distribution. One common choice for sparsity is a Laplace\r\ndistribution. However, due to disadvantages of a Laplacian prior in regards to the SRUKF,\r\nthe regularized horseshoe distribution, a Gaussian that approximately features sparsity, is\r\napplied instead. Results exhibit small estimation errors with model improvements detected by\r\nan automated model reduction technique."}],"issue":"2","publication":"IFAC-PapersOnLine","department":[{"_id":"153"},{"_id":"880"}],"keyword":["joint estimation","unscented Kalman filter","sparsity","Laplacian prior","regularized horseshoe","principal component analysis"],"type":"conference","date_created":"2023-05-02T15:16:43Z","intvolume":" 56","date_updated":"2024-11-13T08:42:37Z","author":[{"full_name":"Götte, Ricarda-Samantha","first_name":"Ricarda-Samantha","last_name":"Götte","id":"43992"},{"id":"15402","full_name":"Timmermann, Julia","first_name":"Julia","last_name":"Timmermann"}],"title":"Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF","year":"2023","language":[{"iso":"eng"}],"quality_controlled":"1","citation":{"mla":"Götte, Ricarda-Samantha, and Julia Timmermann. “Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF.” IFAC-PapersOnLine, vol. 56, no. 2, 2023, pp. 869–74.","ama":"Götte R-S, Timmermann J. Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF. In: IFAC-PapersOnLine. Vol 56. ; 2023:869-874.","bibtex":"@inproceedings{Götte_Timmermann_2023, title={Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF}, volume={56}, number={2}, booktitle={IFAC-PapersOnLine}, author={Götte, Ricarda-Samantha and Timmermann, Julia}, year={2023}, pages={869–874} }","apa":"Götte, R.-S., & Timmermann, J. (2023). Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF. IFAC-PapersOnLine, 56(2), 869–874.","ieee":"R.-S. Götte and J. Timmermann, “Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF,” in IFAC-PapersOnLine, Yokohama, Japan, 2023, vol. 56, no. 2, pp. 869–874.","short":"R.-S. Götte, J. Timmermann, in: IFAC-PapersOnLine, 2023, pp. 869–874.","chicago":"Götte, Ricarda-Samantha, and Julia Timmermann. “Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF.” In IFAC-PapersOnLine, 56:869–74, 2023."},"conference":{"start_date":"2023-07-09","name":"22nd IFAC World Congress","location":"Yokohama, Japan","end_date":"2023-07-14"},"status":"public","volume":56,"user_id":"43992","_id":"44326","page":"869-874"},{"status":"public","page":"232–254","_id":"33849","publisher":"Springer International Publishing","user_id":"552","editor":[{"last_name":"Klein","first_name":"Cornel","full_name":"Klein, Cornel"},{"full_name":"Jarke, Mathias","last_name":"Jarke","first_name":"Mathias"},{"last_name":"Helfert","first_name":"Markus","full_name":"Helfert, Markus"},{"full_name":"Berns, Karsten","first_name":"Karsten","last_name":"Berns"},{"full_name":"Gusikhin, Oleg","first_name":"Oleg","last_name":"Gusikhin"}],"volume":1612,"citation":{"chicago":"Malena, Kevin, Christopher Link, Leon Bußemas, Sandra Gausemeier, and Ansgar Trächtler. “Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments.” In Communications in Computer and Information Science, edited by Cornel Klein, Mathias Jarke, Markus Helfert, Karsten Berns, and Oleg Gusikhin, 1612:232–254. Communications in Computer and Information Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-17098-0_12.","ama":"Malena K, Link C, Bußemas L, Gausemeier S, Trächtler A. Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments. In: Klein C, Jarke M, Helfert M, Berns K, Gusikhin O, eds. Communications in Computer and Information Science. Vol 1612. Communications in Computer and Information Science. Springer International Publishing; 2022:232–254. doi:10.1007/978-3-031-17098-0_12","short":"K. Malena, C. Link, L. Bußemas, S. Gausemeier, A. Trächtler, in: C. Klein, M. Jarke, M. Helfert, K. Berns, O. Gusikhin (Eds.), Communications in Computer and Information Science, Springer International Publishing, Cham, 2022, pp. 232–254.","bibtex":"@inbook{Malena_Link_Bußemas_Gausemeier_Trächtler_2022, place={Cham}, series={Communications in Computer and Information Science}, title={Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments}, volume={1612}, DOI={10.1007/978-3-031-17098-0_12}, booktitle={Communications in Computer and Information Science}, publisher={Springer International Publishing}, author={Malena, Kevin and Link, Christopher and Bußemas, Leon and Gausemeier, Sandra and Trächtler, Ansgar}, editor={Klein, Cornel and Jarke, Mathias and Helfert, Markus and Berns, Karsten and Gusikhin, Oleg}, year={2022}, pages={232–254}, collection={Communications in Computer and Information Science} }","apa":"Malena, K., Link, C., Bußemas, L., Gausemeier, S., & Trächtler, A. (2022). Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments. In C. Klein, M. Jarke, M. Helfert, K. Berns, & O. Gusikhin (Eds.), Communications in Computer and Information Science (Vol. 1612, pp. 232–254). Springer International Publishing. https://doi.org/10.1007/978-3-031-17098-0_12","mla":"Malena, Kevin, et al. “Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments.” Communications in Computer and Information Science, edited by Cornel Klein et al., vol. 1612, Springer International Publishing, 2022, pp. 232–254, doi:10.1007/978-3-031-17098-0_12.","ieee":"K. Malena, C. Link, L. Bußemas, S. Gausemeier, and A. Trächtler, “Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments,” in Communications in Computer and Information Science, vol. 1612, C. Klein, M. Jarke, M. Helfert, K. Berns, and O. Gusikhin, Eds. Cham: Springer International Publishing, 2022, pp. 232–254."},"quality_controlled":"1","place":"Cham","year":"2022","title":"Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments","author":[{"id":"36303","orcid":"0000-0003-1183-4679","last_name":"Malena","first_name":"Kevin","full_name":"Malena, Kevin"},{"first_name":"Christopher","last_name":"Link","full_name":"Link, Christopher","id":"38249"},{"last_name":"Bußemas","first_name":"Leon","full_name":"Bußemas, Leon","id":"51118"},{"full_name":"Gausemeier, Sandra","last_name":"Gausemeier","first_name":"Sandra","id":"17793"},{"id":"552","last_name":"Trächtler","first_name":"Ansgar","full_name":"Trächtler, Ansgar"}],"publication_identifier":{"isbn":["9783031170973","9783031170980"],"issn":["1865-0929","1865-0937"]},"date_updated":"2026-01-26T08:49:52Z","publication_status":"published","intvolume":" 1612","series_title":"Communications in Computer and Information Science","language":[{"iso":"eng"}],"doi":"10.1007/978-3-031-17098-0_12","publication":"Communications in Computer and Information Science","abstract":[{"text":"Modern traffic control systems are key to cope with current and future traffic challenges. In this paper information obtained from a microscopic traffic estimation using various data sources is used to feed a new developed traffic control approach. The presented method can control a traffic area with multiple traffic light systems (TLS) reacting to individual road users and pedestrians. In contrast to widespread green time extension techniques, this control selects the best phase sequence by analyzing the current traffic state reconstructed in SUMO and its predicted progress. To achieve this, the key aspect of the control strategy is to use Model Predictive Control (MPC). In order to maintain realism for real world applications, among other things, the traffic phase transitions are modelled in detail and integrated within the prediction. For the efficiency, the approach incorporates a fuzzy logic preselection of all phases reducing the computational effort. The evaluation itself is able to be easily adjusted to focus on various objectives like low occupancies, reducing waiting times and emissions, few number of phase transitions etc. determining the best switching times for the selected phases. Exemplary traffic simulations demonstrate the functionality of the MPC-based control and, in addition, some aspects under development like the real-world communication network are also discussed.","lang":"eng"}],"related_material":{"record":[{"status":"public","id":"24159","relation":"continues"}]},"date_created":"2022-10-20T15:06:39Z","keyword":["Traffic control","Traffic estimation","Real-time","MPC","Fuzzy","Isolated intersection","Networked intersection","Sensor fusion"],"type":"book_chapter","department":[{"_id":"153"}]},{"citation":{"bibtex":"@inproceedings{Khatibi_Krauter_2021, title={Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD)}, DOI={10.4229/EUPVSEC20212021-5BV.4.11}, booktitle={Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021)}, author={Khatibi, Arash and Krauter, Stefan}, year={2021}, pages={1141–1147} }","ama":"Khatibi A, Krauter S. Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD). In: Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021). ; 2021:1141-1147. doi:10.4229/EUPVSEC20212021-5BV.4.11","mla":"Khatibi, Arash, and Stefan Krauter. “Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD).” Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021), 2021, pp. 1141–47, doi:10.4229/EUPVSEC20212021-5BV.4.11.","chicago":"Khatibi, Arash, and Stefan Krauter. “Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD).” In Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021), 1141–47, 2021. https://doi.org/10.4229/EUPVSEC20212021-5BV.4.11.","short":"A. Khatibi, S. Krauter, in: Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021), 2021, pp. 1141–1147.","ieee":"A. Khatibi and S. Krauter, “Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD),” in Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021), 2021, pp. 1141–1147, doi: 10.4229/EUPVSEC20212021-5BV.4.11.","apa":"Khatibi, A., & Krauter, S. (2021). Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD). Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021), 1141–1147. https://doi.org/10.4229/EUPVSEC20212021-5BV.4.11"},"file_date_updated":"2022-01-06T13:26:47Z","quality_controlled":"1","_id":"24551","page":"1141 - 1147","user_id":"28836","ddc":["550"],"conference":{"name":"38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021)","start_date":"2021-09-06","end_date":"2021-09-10"},"status":"public","has_accepted_license":"1","date_created":"2021-09-16T10:20:41Z","file":[{"creator":"krauter","date_created":"2022-01-06T13:26:47Z","file_size":2475972,"access_level":"closed","file_name":"Khatibi Krauter - MERRA 2 vs Meteonorm - EUPVSEC 2021.pdf","date_updated":"2022-01-06T13:26:47Z","relation":"main_file","content_type":"application/pdf","success":1,"file_id":"29176"}],"department":[{"_id":"53"}],"keyword":["Energy potential estimation","Photovoltaic","Solar radiation","Temperature measurement","Satellite data","Meteonorm","MERRA-2","DWD"],"type":"conference","publication":"Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2021)","abstract":[{"lang":"eng","text":"Access to precise meteorological data is crucial to be able to plan and install renewable energy systems \r\nsuch as solar power plants and wind farms. In case of solar energy, knowledge of local irradiance and air temperature \r\nvalues is very important. For this, various methods can be used such as installing local weather stations or using \r\nmeteorological data from different organizations such as Meteonorm or official Deutscher Wetterdienst (DWD). An \r\nalternative is to use satellite reanalysis datasets provided by organizations like the National Aeronautics and Space \r\nAdministration (NASA) and European Centre for Medium-Range Weather Forecasts (ECMWF). In this paper the \r\n“Modern-Era Retrospective analysis for Research and Applications” dataset version 2 (MERRA-2) will be presented, \r\nand its performance will be evaluated by comparing it to locally measured datasets provided by Meteonorm and DWD. \r\nThe analysis shows very high correlation between MERRA-2 and local measurements (correlation coefficients of 0.99) \r\nfor monthly global irradiance and air temperature values. The results prove the suitability of MERRA-2 data for \r\napplications requiring long historical data. Moreover, availability of MERRA-2 for the whole world with an acceptable \r\nresolution makes it a very valuable dataset."}],"language":[{"iso":"eng"}],"doi":"10.4229/EUPVSEC20212021-5BV.4.11","publication_identifier":{"isbn":["3-936338-78-7"]},"author":[{"id":"43538","full_name":"Khatibi, Arash","first_name":"Arash","last_name":"Khatibi"},{"id":"28836","orcid":"0000-0002-3594-260X","last_name":"Krauter","first_name":"Stefan","full_name":"Krauter, Stefan"}],"title":"Comparison and Validation of Irradiance Data: Satellite Meteorological Dataset MERRA-2 vs. Meteonorm and German Weather Service (DWD)","year":"2021","publication_status":"published","date_updated":"2022-01-06T13:29:51Z"},{"oa":"1","quality_controlled":"1","citation":{"chicago":"Bender, Amelie, and Walter Sextro. “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties.” In Proceedings of the European Conference of the PHM Society 2021, edited by Phuc Do, Steve King, and Olga Fink, Vol. 6, 2021. https://doi.org/10.36001/phme.2021.v6i1.2843 .","short":"A. Bender, W. Sextro, in: P. Do, S. King, Olga Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021, 2021.","ieee":"A. Bender and W. Sextro, “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties,” in Proceedings of the European Conference of the PHM Society 2021, 2021, vol. 6, no. 1, doi: https://doi.org/10.36001/phme.2021.v6i1.2843 .","apa":"Bender, A., & Sextro, W. (2021). Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties. In P. Do, S. King, & Olga Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021 (Vol. 6, Issue 1). https://doi.org/10.36001/phme.2021.v6i1.2843 ","bibtex":"@inproceedings{Bender_Sextro_2021, title={Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties}, volume={6}, DOI={https://doi.org/10.36001/phme.2021.v6i1.2843 }, number={1}, booktitle={Proceedings of the European Conference of the PHM Society 2021}, author={Bender, Amelie and Sextro, Walter}, editor={Do, Phuc and King, Steve and Fink, Olga}, year={2021} }","ama":"Bender A, Sextro W. Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties. In: Do P, King S, Fink Olga, eds. Proceedings of the European Conference of the PHM Society 2021. Vol 6. ; 2021. doi:https://doi.org/10.36001/phme.2021.v6i1.2843 ","mla":"Bender, Amelie, and Walter Sextro. “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties.” Proceedings of the European Conference of the PHM Society 2021, edited by Phuc Do et al., vol. 6, no. 1, 2021, doi:https://doi.org/10.36001/phme.2021.v6i1.2843 ."},"user_id":"54290","editor":[{"full_name":"Do, Phuc ","last_name":"Do","first_name":"Phuc "},{"first_name":"Steve","last_name":"King","full_name":"King, Steve"},{"full_name":"Fink, Olga","last_name":"Fink","first_name":" Olga"}],"volume":6,"_id":"22724","status":"public","conference":{"start_date":"2021-06-28","name":"6th European Conference of Prognostics and Health Management","end_date":"2021-07-02"},"keyword":["Hybrid prediction method","Multi-model particle filtering","Uncertainty quantification","RUL estimation"],"type":"conference","department":[{"_id":"151"}],"date_created":"2021-07-14T06:29:08Z","abstract":[{"lang":"eng","text":"\r\nPredictive Maintenance as a desirable maintenance strategy in industrial applications relies on suitable condition monitoring solutions to reduce costs and risks of the monitored technical systems. In general, those solutions utilize model-based or data-driven methods to diagnose the current state or predict future states of monitored technical systems. However, both methods have their advantages and drawbacks. Combining both methods can improve uncertainty consideration and accuracy. Different combination approaches of those hybrid methods exist to exploit synergy effects. The choice of an appropriate approach depends on different requirements and the goal behind the selection of a hybrid approach.\r\n\r\n \r\n\r\nIn this work, the hybrid approach for estimating remaining useful lifetime takes potential uncertainties into account. Therefore, a data-driven estimation of new measurements is integrated within a model-based method. To consider uncertainties within the system, a differentiation between different system behavior is realized throughout diverse states of degradation.\r\n\r\nThe developed hybrid prediction approach bases on a particle filtering method combined with a machine learning method, to estimate the remaining useful lifetime of technical systems. Particle filtering as a Monte Carlo simulation technique is suitable to map and propagate uncertainties. Moreover, it is a state-of-the-art model-based method for predicting remaining useful lifetime of technical systems. To integrate uncertainties a multi-model particle filtering approach is employed. In general, resampling as a part of the particle filtering approach has the potential to lead to an accurate prediction. However, in the case where no future measurements are available, it may increase the uncertainty of the prediction. By estimating new measurements, those uncertainties are reduced within the data-driven part of the approach. Hence, both parts of the hybrid approach strive to account for and reduce uncertainties.\r\n\r\n \r\n\r\nRubber-metal-elements are employed as a use-case to evaluate the developed approach. Rubber-metal-elements, which are used to isolate vibrations in various systems, such as railways, trucks and wind turbines, show various uncertainties in their behavior and their degradation. Those uncertainties are caused by diverse inner and outer factors, such as manufacturing influences and operating conditions. By expert knowledge the influences are described, analyzed and if possible reduced. However, the remaining uncertainties are considered within the hybrid prediction method. Relative temperature is the selected measurand to describe the element’s degradation. In lifetime tests, it is measured as the difference between the element’s temperature and the ambient temperature. Thereby, the influence of the ambient temperature on the element’s temperature is taken into account. Those elements show three typical states of degradation that are identified within the temperature measurements. Depending on the particular state of degradation a new measurement is estimated within the hybrid approach to reduce potential uncertainties.\r\n\r\nFinally, the performance of the developed hybrid method is compared to a model-based method for estimating the remaining useful lifetime of the same elements. Suitable performance indices are implemented to underline the differences between the results."}],"issue":"1","publication":"Proceedings of the European Conference of the PHM Society 2021","doi":"https://doi.org/10.36001/phme.2021.v6i1.2843 ","main_file_link":[{"url":"https://papers.phmsociety.org/index.php/phme/article/view/2843","open_access":"1"}],"language":[{"iso":"eng"}],"date_updated":"2023-09-22T07:19:48Z","publication_status":"published","intvolume":" 6","year":"2021","title":"Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties","author":[{"last_name":"Bender","first_name":"Amelie","full_name":"Bender, Amelie","id":"54290"},{"first_name":"Walter","last_name":"Sextro","full_name":"Sextro, Walter","id":"21220"}],"publication_identifier":{"unknown":["978-1-936263-34-9"]}},{"series_title":"VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://www.scitepress.org/PublicationsDetail.aspx?ID=3xZWfOSENWk=&t=1"}],"intvolume":" 7","date_updated":"2026-01-26T08:49:53Z","publication_status":"published","author":[{"full_name":"Malena, Kevin","orcid":"0000-0003-1183-4679","last_name":"Malena","first_name":"Kevin","id":"36303"},{"id":"38249","first_name":"Christopher","last_name":"Link","full_name":"Link, Christopher"},{"first_name":"Sven","last_name":"Mertin","full_name":"Mertin, Sven","id":"13195"},{"full_name":"Gausemeier, Sandra","last_name":"Gausemeier","first_name":"Sandra","id":"17793"},{"id":"552","first_name":"Ansgar","last_name":"Trächtler","full_name":"Trächtler, Ansgar"}],"publication_identifier":{"isbn":["978-989-758-513-5"]},"year":"2021","title":"Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*","department":[{"_id":"153"}],"type":"conference","keyword":["Microscopic Traffic Simulation","Online State Estimation","Mixed Road Users","Sensor Fusion","Integer Programming","Route Choice","Vehicle2Infrastructure"],"date_created":"2021-09-10T12:19:14Z","related_material":{"record":[{"relation":"is_continued_by","id":"33849","status":"public"}],"link":[{"url":"https://www.scitepress.org/PublicationsDetail.aspx?ID=3xZWfOSENWk=&t=1","relation":"confirmation"}]},"abstract":[{"text":"The online fitting of a microscopic traffic simulation model to reconstruct the current state of a real traffic\r\narea can be challenging depending on the provided data. This paper presents a novel method based on limited\r\ndata from sensors positioned at specific locations and guarantees a general accordance of reality and\r\nsimulation in terms of multimodal road traffic counts and vehicle speeds. In these considerations, the actual\r\npurpose of research is of particular importance. Here, the research aims at improving the traffic flow by\r\ncontrolling the Traffic Light Systems (TLS) of the examined area which is why the current traffic state and\r\nthe route choices of individual road users are the matter of interest. An integer optimization problem is derived\r\nto fit the current simulation to the latest field measurements. The concept can be transferred to any road traffic\r\nnetwork and results in an observation of the current multimodal traffic state matching at the given sensor\r\nposition. First case studies show promosing results in terms of deviations between reality and simulation.","lang":"eng"}],"publication":"VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems","volume":7,"user_id":"36303","publisher":"SCITEPRESS","_id":"24159","page":"386-395","conference":{"location":"Online Streaming","name":"7th International Conference on Vehicle Technology and Intelligent Transport Systems","start_date":"2021-04-28","end_date":"2021-04-30"},"status":"public","place":"Portugal","project":[{"_id":"688","name":"Pilotprojekt \"Schlosskreuzung\""}],"quality_controlled":"1","citation":{"short":"K. Malena, C. Link, S. Mertin, S. Gausemeier, A. Trächtler, in: VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, SCITEPRESS, Portugal, 2021, pp. 386–395.","chicago":"Malena, Kevin, Christopher Link, Sven Mertin, Sandra Gausemeier, and Ansgar Trächtler. “Online State Estimation for Microscopic Traffic Simulations Using Multiple Data Sources*.” In VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, 7:386–95. VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems. Portugal: SCITEPRESS, 2021.","ieee":"K. Malena, C. Link, S. Mertin, S. Gausemeier, and A. Trächtler, “Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*,” in VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, Online Streaming, 2021, vol. 7, pp. 386–395.","apa":"Malena, K., Link, C., Mertin, S., Gausemeier, S., & Trächtler, A. (2021). Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*. VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, 7, 386–395.","bibtex":"@inproceedings{Malena_Link_Mertin_Gausemeier_Trächtler_2021, place={Portugal}, series={VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems}, title={Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*}, volume={7}, booktitle={VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems}, publisher={SCITEPRESS}, author={Malena, Kevin and Link, Christopher and Mertin, Sven and Gausemeier, Sandra and Trächtler, Ansgar}, year={2021}, pages={386–395}, collection={VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems} }","ama":"Malena K, Link C, Mertin S, Gausemeier S, Trächtler A. Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*. In: VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems. Vol 7. VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems. SCITEPRESS; 2021:386-395.","mla":"Malena, Kevin, et al. “Online State Estimation for Microscopic Traffic Simulations Using Multiple Data Sources*.” VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, vol. 7, SCITEPRESS, 2021, pp. 386–95."}},{"user_id":"55222","doi":"10.1109/TR.2017.2710260","_id":"9978","language":[{"iso":"eng"}],"page":"1 - 10","date_updated":"2019-09-16T10:32:05Z","author":[{"first_name":"James Kuria","last_name":"Kimotho","full_name":"Kimotho, James Kuria"},{"id":"21220","last_name":"Sextro","first_name":"Walter","full_name":"Sextro, Walter"},{"id":"210","last_name":"Hemsel","first_name":"Tobias","full_name":"Hemsel, Tobias"}],"status":"public","title":"Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing","year":"2017","department":[{"_id":"151"}],"keyword":["Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing"],"type":"conference","date_created":"2019-05-27T09:41:06Z","abstract":[{"lang":"eng","text":"Piezoelectric transducers are used in a wide range of applications. Reliability of these transducers is an important aspect in their application. Prognostics, which involve continuous monitoring of the health of technical systems and using this information to estimate the current health state and consequently predict the remaining useful lifetime (RUL), can be used to increase the reliability, safety, and availability of the transducers. This is achieved by utilizing the health state and RUL predictions to adaptively control the usage of the components or to schedule appropriate maintenance without interrupting operation. In this work, a prognostic approach utilizing self-sensing, where electric signals of a piezoelectric transducer are used as the condition monitoring data, is proposed. The approach involves training machine learning algorithms to model the degradation of the transducers through a health index and the use of the learned model to estimate the health index of similar transducers. The current health index is then used to estimate RUL of test components. The feasibility of the approach is demonstrated using piezoelectric bimorphs and the results show that the method is accurate in predicting the health index and RUL."}],"quality_controlled":"1","citation":{"apa":"Kimotho, J. K., Sextro, W., & Hemsel, T. (2017). Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing. In IEEE Transactions on Reliability (pp. 1–10). https://doi.org/10.1109/TR.2017.2710260","ieee":"J. K. Kimotho, W. Sextro, and T. Hemsel, “Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing,” in IEEE Transactions on Reliability, 2017, pp. 1–10.","short":"J.K. Kimotho, W. Sextro, T. Hemsel, in: IEEE Transactions on Reliability, 2017, pp. 1–10.","chicago":"Kimotho, James Kuria, Walter Sextro, and Tobias Hemsel. “Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing.” In IEEE Transactions on Reliability, 1–10, 2017. https://doi.org/10.1109/TR.2017.2710260.","mla":"Kimotho, James Kuria, et al. “Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing.” IEEE Transactions on Reliability, 2017, pp. 1–10, doi:10.1109/TR.2017.2710260.","ama":"Kimotho JK, Sextro W, Hemsel T. Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing. In: IEEE Transactions on Reliability. ; 2017:1-10. doi:10.1109/TR.2017.2710260","bibtex":"@inproceedings{Kimotho_Sextro_Hemsel_2017, title={Estimation of Remaining Useful Lifetime of Piezoelectric Transducers Based on Self-Sensing}, DOI={10.1109/TR.2017.2710260}, booktitle={IEEE Transactions on Reliability}, author={Kimotho, James Kuria and Sextro, Walter and Hemsel, Tobias}, year={2017}, pages={1–10} }"},"publication":"IEEE Transactions on Reliability"},{"type":"conference","keyword":["ageing","particle filtering (numerical methods)","proton exchange membrane fuel cells","remaining life assessment","PEM fuel cell prognostics","PHM","RUL predictions","accelerated degradation","adaptive particle filter algorithm","dynamic loading","model parameter adaptation","prognostics and health management","proton exchange membrane fuel cells","remaining useful life estimation","self-healing effect","Adaptation models","Data models","Degradation","Estimation","Fuel cells","Mathematical model","Prognostics and health management"],"department":[{"_id":"151"}],"date_created":"2019-05-20T13:11:02Z","abstract":[{"text":"Application of prognostics and health management (PHM) in the field of Proton Exchange Membrane (PEM) fuel cells is emerging as an important tool in increasing the reliability and availability of these systems. Though a lot of work is currently being conducted to develop PHM systems for fuel cells, various challenges have been encountered including the self-healing effect after characterization as well as accelerated degradation due to dynamic loading, all which make RUL predictions a difficult task. In this study, a prognostic approach based on adaptive particle filter algorithm is proposed. The novelty of the proposed method lies in the introduction of a self-healing factor after each characterization and the adaption of the degradation model parameters to fit to the changing degradation trend. An ensemble of five different state models based on weighted mean is then developed. The results show that the method is effective in estimating the remaining useful life of PEM fuel cells, with majority of the predictions falling within 5\\% error. The method was employed in the IEEE 2014 PHM Data Challenge and led to our team emerging the winner of the RUL category of the challenge.","lang":"eng"}],"publication":"Prognostics and Health Management (PHM), 2014 IEEE Conference on","citation":{"mla":"Kimotho, James Kuria, et al. “PEM Fuel Cell Prognostics Using Particle Filter with Model Parameter Adaptation.” Prognostics and Health Management (PHM), 2014 IEEE Conference On, 2014, pp. 1–6, doi:10.1109/ICPHM.2014.7036406.","bibtex":"@inproceedings{Kimotho_Meyer_Sextro_2014, title={PEM fuel cell prognostics using particle filter with model parameter adaptation}, DOI={10.1109/ICPHM.2014.7036406}, booktitle={Prognostics and Health Management (PHM), 2014 IEEE Conference on}, author={Kimotho, James Kuria and Meyer, Tobias and Sextro, Walter}, year={2014}, pages={1–6} }","ama":"Kimotho JK, Meyer T, Sextro W. PEM fuel cell prognostics using particle filter with model parameter adaptation. In: Prognostics and Health Management (PHM), 2014 IEEE Conference On. ; 2014:1-6. doi:10.1109/ICPHM.2014.7036406","ieee":"J. K. Kimotho, T. Meyer, and W. Sextro, “PEM fuel cell prognostics using particle filter with model parameter adaptation,” in Prognostics and Health Management (PHM), 2014 IEEE Conference on, 2014, pp. 1–6.","apa":"Kimotho, J. K., Meyer, T., & Sextro, W. (2014). PEM fuel cell prognostics using particle filter with model parameter adaptation. In Prognostics and Health Management (PHM), 2014 IEEE Conference on (pp. 1–6). https://doi.org/10.1109/ICPHM.2014.7036406","short":"J.K. Kimotho, T. Meyer, W. Sextro, in: Prognostics and Health Management (PHM), 2014 IEEE Conference On, 2014, pp. 1–6.","chicago":"Kimotho, James Kuria , Tobias Meyer, and Walter Sextro. “PEM Fuel Cell Prognostics Using Particle Filter with Model Parameter Adaptation.” In Prognostics and Health Management (PHM), 2014 IEEE Conference On, 1–6, 2014. https://doi.org/10.1109/ICPHM.2014.7036406."},"doi":"10.1109/ICPHM.2014.7036406","user_id":"55222","page":"1-6","language":[{"iso":"eng"}],"_id":"9879","date_updated":"2019-05-20T13:12:27Z","title":"PEM fuel cell prognostics using particle filter with model parameter adaptation","status":"public","year":"2014","author":[{"last_name":"Kimotho","first_name":"James Kuria ","full_name":"Kimotho, James Kuria "},{"last_name":"Meyer","first_name":"Tobias","full_name":"Meyer, Tobias"},{"last_name":"Sextro","first_name":"Walter","full_name":"Sextro, Walter","id":"21220"}]},{"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2014/DrChTrHaeb14.pdf","open_access":"1"}],"page":"213-217","language":[{"iso":"eng"}],"_id":"11753","user_id":"44006","year":"2014","title":"Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models","status":"public","author":[{"id":"11213","full_name":"Drude, Lukas","first_name":"Lukas","last_name":"Drude"},{"last_name":"Chinaev","first_name":"Aleksej","full_name":"Chinaev, Aleksej"},{"full_name":"Tran Vu, Dang Hai","first_name":"Dang Hai","last_name":"Tran Vu"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"date_updated":"2022-01-06T06:51:08Z","date_created":"2019-07-12T05:27:35Z","keyword":["Accuracy","Acoustics","Estimation","Mathematical model","Soruce separation","Speech","Vectors","Bayes methods","Blind source separation","Directional statistics","Number of speakers","Speaker diarization"],"type":"conference","department":[{"_id":"54"}],"oa":"1","publication":"14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)","citation":{"ama":"Drude L, Chinaev A, Tran Vu DH, Haeb-Umbach R. Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models. In: 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014). ; 2014:213-217.","bibtex":"@inproceedings{Drude_Chinaev_Tran Vu_Haeb-Umbach_2014, title={Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models}, booktitle={14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)}, author={Drude, Lukas and Chinaev, Aleksej and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2014}, pages={213–217} }","mla":"Drude, Lukas, et al. “Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models.” 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014), 2014, pp. 213–17.","chicago":"Drude, Lukas, Aleksej Chinaev, Dang Hai Tran Vu, and Reinhold Haeb-Umbach. “Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models.” In 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014), 213–17, 2014.","short":"L. Drude, A. Chinaev, D.H. Tran Vu, R. Haeb-Umbach, in: 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014), 2014, pp. 213–217.","apa":"Drude, L., Chinaev, A., Tran Vu, D. H., & Haeb-Umbach, R. (2014). Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models. In 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014) (pp. 213–217).","ieee":"L. Drude, A. Chinaev, D. H. Tran Vu, and R. Haeb-Umbach, “Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models,” in 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014), 2014, pp. 213–217."},"related_material":{"link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2014/DrChTrHaeb14_Poster.pdf","relation":"supplementary_material","description":"Poster"}]},"abstract":[{"lang":"eng","text":"This contribution describes a step-wise source counting algorithm to determine the number of speakers in an offline scenario. Each speaker is identified by a variational expectation maximization (VEM) algorithm for complex Watson mixture models and therefore directly yields beamforming vectors for a subsequent speech separation process. An observation selection criterion is proposed which improves the robustness of the source counting in noise. The algorithm is compared to an alternative VEM approach with Gaussian mixture models based on directions of arrival and shown to deliver improved source counting accuracy. The article concludes by extending the offline algorithm towards a low-latency online estimation of the number of active sources from the streaming input data."}]},{"doi":"10.1109/ICASSP.2013.6638984","user_id":"44006","language":[{"iso":"eng"}],"_id":"11716","page":"6827-6831","date_updated":"2022-01-06T06:51:07Z","publication_identifier":{"issn":["1520-6149"]},"author":[{"last_name":"Abdelaziz","first_name":"Ahmed H.","full_name":"Abdelaziz, Ahmed H."},{"full_name":"Zeiler, Steffen","last_name":"Zeiler","first_name":"Steffen"},{"first_name":"Dorothea","last_name":"Kolossa","full_name":"Kolossa, Dorothea"},{"last_name":"Leutnant","first_name":"Volker","full_name":"Leutnant, Volker"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"}],"title":"GMM-based significance decoding","year":"2013","status":"public","department":[{"_id":"54"}],"type":"conference","keyword":["Bayes methods","Gaussian processes","convolution","decision theory","decoding","noise","reverberation","speech coding","speech recognition","Bayesian decision rule","GMM","Gaussian mixture models","additive noise scenarios","automatic speech recognition systems","convolutive noise scenarios","decoding approach","mathematical framework","reverberant environments","significance decoding","speech feature estimation","uncertainty-of-observation techniques","Hidden Markov models","Maximum likelihood decoding","Noise","Speech","Speech recognition","Uncertainty","Uncertainty-of-observation","modified imputation","noise robust speech recognition","significance decoding","uncertainty decoding"],"date_created":"2019-07-12T05:26:53Z","abstract":[{"text":"The accuracy of automatic speech recognition systems in noisy and reverberant environments can be improved notably by exploiting the uncertainty of the estimated speech features using so-called uncertainty-of-observation techniques. In this paper, we introduce a new Bayesian decision rule that can serve as a mathematical framework from which both known and new uncertainty-of-observation techniques can be either derived or approximated. The new decision rule in its direct form leads to the new significance decoding approach for Gaussian mixture models, which results in better performance compared to standard uncertainty-of-observation techniques in different additive and convolutive noise scenarios.","lang":"eng"}],"citation":{"ama":"Abdelaziz AH, Zeiler S, Kolossa D, Leutnant V, Haeb-Umbach R. GMM-based significance decoding. In: Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On. ; 2013:6827-6831. doi:10.1109/ICASSP.2013.6638984","bibtex":"@inproceedings{Abdelaziz_Zeiler_Kolossa_Leutnant_Haeb-Umbach_2013, title={GMM-based significance decoding}, DOI={10.1109/ICASSP.2013.6638984}, booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on}, author={Abdelaziz, Ahmed H. and Zeiler, Steffen and Kolossa, Dorothea and Leutnant, Volker and Haeb-Umbach, Reinhold}, year={2013}, pages={6827–6831} }","mla":"Abdelaziz, Ahmed H., et al. “GMM-Based Significance Decoding.” Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On, 2013, pp. 6827–31, doi:10.1109/ICASSP.2013.6638984.","short":"A.H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, R. Haeb-Umbach, in: Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On, 2013, pp. 6827–6831.","chicago":"Abdelaziz, Ahmed H., Steffen Zeiler, Dorothea Kolossa, Volker Leutnant, and Reinhold Haeb-Umbach. “GMM-Based Significance Decoding.” In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On, 6827–31, 2013. https://doi.org/10.1109/ICASSP.2013.6638984.","apa":"Abdelaziz, A. H., Zeiler, S., Kolossa, D., Leutnant, V., & Haeb-Umbach, R. (2013). GMM-based significance decoding. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 6827–6831). https://doi.org/10.1109/ICASSP.2013.6638984","ieee":"A. H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, and R. Haeb-Umbach, “GMM-based significance decoding,” in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on, 2013, pp. 6827–6831."},"publication":"Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on"},{"oa":"1","citation":{"chicago":"Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.” In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 3352–56, 2013. https://doi.org/10.1109/ICASSP.2013.6638279.","ama":"Chinaev A, Haeb-Umbach R. MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations. In: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). ; 2013:3352-3356. doi:10.1109/ICASSP.2013.6638279","short":"A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.","bibtex":"@inproceedings{Chinaev_Haeb-Umbach_2013, title={MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations}, DOI={10.1109/ICASSP.2013.6638279}, booktitle={38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2013}, pages={3352–3356} }","mla":"Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.” 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–56, doi:10.1109/ICASSP.2013.6638279.","apa":"Chinaev, A., & Haeb-Umbach, R. (2013). MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations. In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) (pp. 3352–3356). https://doi.org/10.1109/ICASSP.2013.6638279","ieee":"A. Chinaev and R. Haeb-Umbach, “MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations,” in 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356."},"user_id":"44006","page":"3352-3356","_id":"11740","status":"public","keyword":["Gaussian noise","maximum likelihood estimation","parameter estimation","GMM parameter","Gaussian mixture model","MAP estimation","Map-based estimation","maximum a-posteriori estimation","maximum likelihood technique","noisy observation","sequential estimation framework","white Gaussian noise","Additive noise","Gaussian mixture model","Maximum likelihood estimation","Noise measurement","Gaussian mixture model","Maximum a posteriori estimation","Maximum likelihood estimation"],"type":"conference","department":[{"_id":"54"}],"date_created":"2019-07-12T05:27:20Z","abstract":[{"text":"In this contribution we derive the Maximum A-Posteriori (MAP) estimates of the parameters of a Gaussian Mixture Model (GMM) in the presence of noisy observations. We assume the distortion to be white Gaussian noise of known mean and variance. An approximate conjugate prior of the GMM parameters is derived allowing for a computationally efficient implementation in a sequential estimation framework. Simulations on artificially generated data demonstrate the superiority of the proposed method compared to the Maximum Likelihood technique and to the ordinary MAP approach, whose estimates are corrected by the known statistics of the distortion in a straightforward manner.","lang":"eng"}],"related_material":{"link":[{"description":"Poster","relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13_Poster.pdf"}]},"publication":"38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)","doi":"10.1109/ICASSP.2013.6638279","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13.pdf"}],"language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:51:08Z","title":"MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations","year":"2013","author":[{"full_name":"Chinaev, Aleksej","last_name":"Chinaev","first_name":"Aleksej"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"publication_identifier":{"issn":["1520-6149"]}},{"oa":"1","citation":{"short":"M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.","ama":"Hoang MK, Haeb-Umbach R. Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning. In: 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013). ; 2013:3721-3725. doi:10.1109/ICASSP.2013.6638353","chicago":"Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification of Censored Gaussian Data with Application to WiFi Indoor Positioning.” In 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 3721–25, 2013. https://doi.org/10.1109/ICASSP.2013.6638353.","bibtex":"@inproceedings{Hoang_Haeb-Umbach_2013, title={Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning}, DOI={10.1109/ICASSP.2013.6638353}, booktitle={38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)}, author={Hoang, Manh Kha and Haeb-Umbach, Reinhold}, year={2013}, pages={3721–3725} }","mla":"Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification of Censored Gaussian Data with Application to WiFi Indoor Positioning.” 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–25, doi:10.1109/ICASSP.2013.6638353.","apa":"Hoang, M. K., & Haeb-Umbach, R. (2013). Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning. In 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013) (pp. 3721–3725). https://doi.org/10.1109/ICASSP.2013.6638353","ieee":"M. K. Hoang and R. Haeb-Umbach, “Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning,” in 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725."},"_id":"11816","page":"3721-3725","user_id":"44006","status":"public","date_created":"2019-07-12T05:28:48Z","department":[{"_id":"54"}],"type":"conference","keyword":["Gaussian processes","Global Positioning System","convergence","expectation-maximisation algorithm","fingerprint identification","indoor radio","signal classification","wireless LAN","EM algorithm","ML estimation","WiFi indoor positioning","censored Gaussian data classification","clipped data","convergence properties","expectation maximization algorithm","fingerprinting method","maximum likelihood estimation","optimal classification","parameters estimation","portable devices sensitivity","signal strength measurements","wireless LAN positioning systems","Convergence","IEEE 802.11 Standards","Maximum likelihood estimation","Parameter estimation","Position measurement","Training","Indoor positioning","censored data","expectation maximization","signal strength","wireless LAN"],"publication":"38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)","related_material":{"link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013_Poster.pdf","relation":"supplementary_material","description":"Poster"}]},"abstract":[{"text":"In this paper, we consider the Maximum Likelihood (ML) estimation of the parameters of a GAUSSIAN in the presence of censored, i.e., clipped data. We show that the resulting Expectation Maximization (EM) algorithm delivers virtually biasfree and efficient estimates, and we discuss its convergence properties. We also discuss optimal classification in the presence of censored data. Censored data are frequently encountered in wireless LAN positioning systems based on the fingerprinting method employing signal strength measurements, due to the limited sensitivity of the portable devices. Experiments both on simulated and real-world data demonstrate the effectiveness of the proposed algorithms.","lang":"eng"}],"language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013.pdf"}],"doi":"10.1109/ICASSP.2013.6638353","publication_identifier":{"issn":["1520-6149"]},"author":[{"full_name":"Hoang, Manh Kha","first_name":"Manh Kha","last_name":"Hoang"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"title":"Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning","year":"2013","date_updated":"2022-01-06T06:51:09Z"},{"department":[{"_id":"54"}],"type":"conference","keyword":["correlation methods","estimation theory","hidden Markov models","iterative methods","probability","spectral analysis","speech processing","2D HMM","SPP estimates","iterative algorithm","posterior probability estimation","spectral correlation","speech presence probability estimation","state-of-the-art SPP estimation algorithm","temporal correlation","turbo principle","two-dimensional hidden Markov model","Correlation","Decoding","Estimation","Iterative decoding","Noise","Speech","Vectors"],"date_created":"2019-07-12T05:30:45Z","abstract":[{"text":"In this paper we present a speech presence probability (SPP) estimation algorithmwhich exploits both temporal and spectral correlations of speech. To this end, the SPP estimation is formulated as the posterior probability estimation of the states of a two-dimensional (2D) Hidden Markov Model (HMM). We derive an iterative algorithm to decode the 2D-HMM which is based on the turbo principle. The experimental results show that indeed the SPP estimates improve from iteration to iteration, and further clearly outperform another state-of-the-art SPP estimation algorithm.","lang":"eng"}],"citation":{"ama":"Vu DHT, Haeb-Umbach R. Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation. In: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). ; 2013:863-867. doi:10.1109/ICASSP.2013.6637771","short":"D.H.T. Vu, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.","chicago":"Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle for Exploiting Temporal and Spectral Correlations in Speech Presence Probability Estimation.” In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 863–67, 2013. https://doi.org/10.1109/ICASSP.2013.6637771.","bibtex":"@inproceedings{Vu_Haeb-Umbach_2013, title={Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation}, DOI={10.1109/ICASSP.2013.6637771}, booktitle={38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)}, author={Vu, Dang Hai Tran and Haeb-Umbach, Reinhold}, year={2013}, pages={863–867} }","mla":"Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle for Exploiting Temporal and Spectral Correlations in Speech Presence Probability Estimation.” 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–67, doi:10.1109/ICASSP.2013.6637771.","apa":"Vu, D. H. T., & Haeb-Umbach, R. (2013). Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation. In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) (pp. 863–867). https://doi.org/10.1109/ICASSP.2013.6637771","ieee":"D. H. T. Vu and R. Haeb-Umbach, “Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation,” in 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867."},"publication":"38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)","user_id":"44006","doi":"10.1109/ICASSP.2013.6637771","_id":"11917","language":[{"iso":"eng"}],"page":"863-867","date_updated":"2022-01-06T06:51:12Z","author":[{"last_name":"Vu","first_name":"Dang Hai Tran","full_name":"Vu, Dang Hai Tran"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"}],"publication_identifier":{"issn":["1520-6149"]},"year":"2013","status":"public","title":"Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation"},{"date_updated":"2022-01-06T06:51:08Z","author":[{"last_name":"Chinaev","first_name":"Aleksej","full_name":"Chinaev, Aleksej"},{"first_name":"Alexander","last_name":"Krueger","full_name":"Krueger, Alexander"},{"first_name":"Dang Hai","last_name":"Tran Vu","full_name":"Tran Vu, Dang Hai"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"title":"Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor","status":"public","year":"2012","user_id":"44006","language":[{"iso":"eng"}],"_id":"11745","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12.pdf","open_access":"1"}],"related_material":{"link":[{"relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12_Talk.pdf","description":"Presentation"}]},"abstract":[{"text":"In this paper we present a novel noise power spectral density tracking algorithm and its use in single-channel speech enhancement. It has the unique feature that it is able to track the noise statistics even if speech is dominant in a given time-frequency bin. As a consequence it can follow non-stationary noise superposed by speech, even in the critical case of rising noise power. The algorithm requires an initial estimate of the power spectrum of speech and is thus meant to be used as a postprocessor to a first speech enhancement stage. An experimental comparison with a state-of-the-art noise tracking algorithm demonstrates lower estimation errors under low SNR conditions and smaller fluctuations of the estimated values, resulting in improved speech quality as measured by PESQ scores.","lang":"eng"}],"citation":{"mla":"Chinaev, Aleksej, et al. “Improved Noise Power Spectral Density Tracking by a MAP-Based Postprocessor.” 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.","bibtex":"@inproceedings{Chinaev_Krueger_Tran Vu_Haeb-Umbach_2012, title={Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor}, booktitle={37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)}, author={Chinaev, Aleksej and Krueger, Alexander and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2012} }","ama":"Chinaev A, Krueger A, Tran Vu DH, Haeb-Umbach R. Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor. In: 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012). ; 2012.","ieee":"A. Chinaev, A. Krueger, D. H. Tran Vu, and R. Haeb-Umbach, “Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor,” in 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.","apa":"Chinaev, A., Krueger, A., Tran Vu, D. H., & Haeb-Umbach, R. (2012). Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor. In 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012).","short":"A. Chinaev, A. Krueger, D.H. Tran Vu, R. Haeb-Umbach, in: 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.","chicago":"Chinaev, Aleksej, Alexander Krueger, Dang Hai Tran Vu, and Reinhold Haeb-Umbach. “Improved Noise Power Spectral Density Tracking by a MAP-Based Postprocessor.” In 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012."},"publication":"37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)","oa":"1","department":[{"_id":"54"}],"keyword":["MAP parameter estimation","noise power estimation","speech enhancement"],"type":"conference","date_created":"2019-07-12T05:27:26Z"},{"abstract":[{"text":"The paper proposes a modification of the standard maximum a posteriori (MAP) method for the estimation of the parameters of a Gaussian process for cases where the process is superposed by additive Gaussian observation errors of known variance. Simulations on artificially generated data demonstrate the superiority of the proposed method. While reducing to the ordinary MAP approach in the absence of observation noise, the improvement becomes the more pronounced the larger the variance of the observation noise. The method is further extended to track the parameters in case of non-stationary Gaussian processes.","lang":"eng"}],"citation":{"short":"A. Krueger, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.","chicago":"Krueger, Alexander, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of Non-Stationary Gaussian Processes from Noisy Observations.” In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 3596–99, 2011. https://doi.org/10.1109/ICASSP.2011.5946256.","apa":"Krueger, A., & Haeb-Umbach, R. (2011). MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011) (pp. 3596–3599). https://doi.org/10.1109/ICASSP.2011.5946256","ieee":"A. Krueger and R. Haeb-Umbach, “MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.","ama":"Krueger A, Haeb-Umbach R. MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011). ; 2011:3596-3599. doi:10.1109/ICASSP.2011.5946256","bibtex":"@inproceedings{Krueger_Haeb-Umbach_2011, title={MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations}, DOI={10.1109/ICASSP.2011.5946256}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)}, author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2011}, pages={3596–3599} }","mla":"Krueger, Alexander, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of Non-Stationary Gaussian Processes from Noisy Observations.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–99, doi:10.1109/ICASSP.2011.5946256."},"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)","department":[{"_id":"54"}],"oa":"1","keyword":["Gaussian processes","MAP-based estimation","maximum a posteriori method","maximum likelihood estimation","nonstationary Gaussian processes"],"type":"conference","date_created":"2019-07-12T05:29:22Z","date_updated":"2022-01-06T06:51:11Z","author":[{"first_name":"Alexander","last_name":"Krueger","full_name":"Krueger, Alexander"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"year":"2011","status":"public","title":"MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations","user_id":"44006","doi":"10.1109/ICASSP.2011.5946256","_id":"11845","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2011/KrHa11.pdf"}],"page":"3596-3599"},{"citation":{"mla":"Krueger, Alexander, et al. “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation.” IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, 2011, pp. 206–19, doi:10.1109/TASL.2010.2047324.","bibtex":"@article{Krueger_Warsitz_Haeb-Umbach_2011, title={Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation}, volume={19}, DOI={10.1109/TASL.2010.2047324}, number={1}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2011}, pages={206–219} }","ama":"Krueger A, Warsitz E, Haeb-Umbach R. Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation. IEEE Transactions on Audio, Speech, and Language Processing. 2011;19(1):206-219. doi:10.1109/TASL.2010.2047324","ieee":"A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, pp. 206–219, 2011.","apa":"Krueger, A., Warsitz, E., & Haeb-Umbach, R. (2011). Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation. IEEE Transactions on Audio, Speech, and Language Processing, 19(1), 206–219. https://doi.org/10.1109/TASL.2010.2047324","short":"A. Krueger, E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 19 (2011) 206–219.","chicago":"Krueger, Alexander, Ernst Warsitz, and Reinhold Haeb-Umbach. “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation.” IEEE Transactions on Audio, Speech, and Language Processing 19, no. 1 (2011): 206–19. https://doi.org/10.1109/TASL.2010.2047324."},"oa":"1","status":"public","_id":"11850","page":"206-219","volume":19,"user_id":"44006","publication":"IEEE Transactions on Audio, Speech, and Language Processing","issue":"1","abstract":[{"text":"In this paper, we present a novel blocking matrix and fixed beamformer design for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure. They are based on a new method for estimating the acoustical transfer function ratios in the presence of stationary noise. The estimation method relies on solving a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector tracking utilizing the power iteration method is employed and shown to achieve a high convergence speed. Simulation results demonstrate that the proposed beamformer leads to better noise and interference reduction and reduced speech distortions compared to other blocking matrix designs from the literature.","lang":"eng"}],"date_created":"2019-07-12T05:29:28Z","department":[{"_id":"54"}],"keyword":["acoustical transfer function ratio","adaptive eigenvector tracking","array signal processing","beamformer design","blocking matrix","eigenvalues and eigenfunctions","eigenvector-based transfer function ratios estimation","generalized sidelobe canceler","interference reduction","iterative methods","power iteration method","reduced speech distortions","reverberant enclosure","reverberation","speech enhancement","stationary noise"],"type":"journal_article","author":[{"full_name":"Krueger, Alexander","first_name":"Alexander","last_name":"Krueger"},{"last_name":"Warsitz","first_name":"Ernst","full_name":"Warsitz, Ernst"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"year":"2011","title":"Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation","intvolume":" 19","date_updated":"2022-01-06T06:51:11Z","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2011/KrWaHa11.pdf"}],"doi":"10.1109/TASL.2010.2047324"}]