[{"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."}],"user_id":"43992","author":[{"id":"43992","last_name":"Götte","full_name":"Götte, Ricarda-Samantha","first_name":"Ricarda-Samantha"},{"full_name":"Timmermann, Julia","first_name":"Julia","id":"15402","last_name":"Timmermann"}],"quality_controlled":"1","keyword":["joint estimation","unscented Kalman filter","sparsity","Laplacian prior","regularized horseshoe","principal component analysis"],"publication":"IFAC-PapersOnLine","status":"public","date_created":"2023-05-02T15:16:43Z","volume":56,"_id":"44326","intvolume":" 56","conference":{"end_date":"2023-07-14","name":"22nd IFAC World Congress","start_date":"2023-07-09","location":"Yokohama, Japan"},"issue":"2","year":"2023","citation":{"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.","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.","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.","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.","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} }","short":"R.-S. Götte, J. Timmermann, in: IFAC-PapersOnLine, 2023, pp. 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."},"type":"conference","page":"869-874","title":"Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF","department":[{"_id":"153"}],"date_updated":"2023-11-27T07:42:51Z","language":[{"iso":"eng"}]},{"_id":"11930","intvolume":" 4","page":"iv/797-iv/800 Vol. 4","citation":{"ieee":"E. Warsitz and R. Haeb-Umbach, “Acoustic filter-and-sum beamforming by adaptive principal component analysis,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), 2005, vol. 4, p. iv/797-iv/800 Vol. 4.","short":"E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), 2005, p. iv/797-iv/800 Vol. 4.","bibtex":"@inproceedings{Warsitz_Haeb-Umbach_2005, title={Acoustic filter-and-sum beamforming by adaptive principal component analysis}, volume={4}, DOI={10.1109/ICASSP.2005.1416129}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2005}, pages={iv/797-iv/800 Vol. 4} }","mla":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming by Adaptive Principal Component Analysis.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), vol. 4, 2005, p. iv/797-iv/800 Vol. 4, doi:10.1109/ICASSP.2005.1416129.","ama":"Warsitz E, Haeb-Umbach R. Acoustic filter-and-sum beamforming by adaptive principal component analysis. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005). Vol 4. ; 2005:iv/797-iv/800 Vol. 4. doi:10.1109/ICASSP.2005.1416129","apa":"Warsitz, E., & Haeb-Umbach, R. (2005). Acoustic filter-and-sum beamforming by adaptive principal component analysis. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005) (Vol. 4, p. iv/797-iv/800 Vol. 4). https://doi.org/10.1109/ICASSP.2005.1416129","chicago":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming by Adaptive Principal Component Analysis.” In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), 4:iv/797-iv/800 Vol. 4, 2005. https://doi.org/10.1109/ICASSP.2005.1416129."},"year":"2005","type":"conference","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2005/WaHa05.pdf","open_access":"1"}],"user_id":"44006","abstract":[{"lang":"eng","text":"For human-machine interfaces in distant-talking environments multichannel signal processing is often employed to obtain an enhanced signal for subsequent processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum beamformer to adjust the coefficients of FIR filters to changing acoustic room impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient ascent algorithm are derived from a constrained optimization problem, which iteratively estimates the eigenvector corresponding to the largest eigenvalue of the cross power spectral density of the microphone signals. The method does not require an explicit estimation of the speaker location. The experimental results show fast adaptation and excellent robustness of the proposed algorithm."}],"volume":4,"date_created":"2019-07-12T05:31:00Z","status":"public","keyword":["acoustic filter-and-sum beamforming","acoustic room impulses","acoustic signal processing","adaptive principal component analysis","adaptive signal processing","architectural acoustics","constrained optimization problem","cross power spectral density","deterministic algorithm","deterministic algorithms","distant-talking environments","eigenvalues and eigenfunctions","eigenvector","enhanced signal","filter-and-sum beamformer","FIR filter coefficients","FIR filter coefficients","FIR filters","gradient methods","human-machine interfaces","iterative estimation","iterative methods","largest eigenvalue","microphone signals","multichannel signal processing","optimisation","principal component analysis","spectral analysis","stochastic gradient ascent algorithm","stochastic processes"],"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)","author":[{"last_name":"Warsitz","first_name":"Ernst","full_name":"Warsitz, Ernst"},{"id":"242","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold"}],"doi":"10.1109/ICASSP.2005.1416129","oa":"1","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"title":"Acoustic filter-and-sum beamforming by adaptive principal component analysis","department":[{"_id":"54"}]}]