@article{53262, author = {{Santamaria, Ignacio and Soleymani, Mohammad and Jorswieck, Eduard and Gutiérrez, Jesús}}, issn = {{1070-9908}}, journal = {{IEEE Signal Processing Letters}}, keywords = {{Applied Mathematics, Electrical and Electronic Engineering, Signal Processing}}, pages = {{923--926}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{SNR Maximization in Beyond Diagonal RIS-Assisted Single and Multiple Antenna Links}}}, doi = {{10.1109/lsp.2023.3296902}}, volume = {{30}}, year = {{2023}}, } @article{53265, author = {{Soleymani, Mohammad and Santamaria, Ignacio and Jorswieck, Eduard and Rezvani, Sepehr}}, issn = {{1053-587X}}, journal = {{IEEE Transactions on Signal Processing}}, keywords = {{Electrical and Electronic Engineering, Signal Processing}}, pages = {{963--978}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{NOMA-Based Improper Signaling for Multicell MISO RIS-Assisted Broadcast Channels}}}, doi = {{10.1109/tsp.2023.3259145}}, volume = {{71}}, year = {{2023}}, } @article{34046, author = {{Hoffmann, Christin and Thommes, Kirsten}}, issn = {{2168-2291}}, journal = {{IEEE Transactions on Human-Machine Systems}}, keywords = {{Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Human-Computer Interaction, Signal Processing, Control and Systems Engineering, Human Factors and Ergonomics}}, pages = {{1--11}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{Seizing the Opportunity for Automation—How Traffic Density Determines Truck Drivers' Use of Cruise Control}}}, doi = {{10.1109/thms.2022.3212335}}, year = {{2022}}, } @article{29204, abstract = {{An analysis of an optical Nyquist pulse synthesizer using Mach-Zehnder modulators is presented. The analysis allows to predict the upper limit of the effective number of bits of this type of photonic digital-to-analog converter. The analytical solution has been verified by means of electro-optic simulations. With this analysis the limiting factor for certain scenarios: relative intensity noise, distortions by driving the Mach-Zehnder modulator, or the signal generator phase noise can quickly be identified.}}, author = {{Kress, Christian and Bahmanian, Meysam and Schwabe, Tobias and Scheytt, J. Christoph}}, journal = {{Opt. Express}}, keywords = {{Analog to digital converters, Diode lasers, Laser sources, Phase noise, Signal processing, Wavelength division multiplexers}}, number = {{15}}, pages = {{23671–23681}}, publisher = {{OSA}}, title = {{{Analysis of the effects of jitter, relative intensity noise, and nonlinearity on a photonic digital-to-analog converter based on optical Nyquist pulse synthesis}}}, doi = {{10.1364/OE.427424}}, volume = {{29}}, year = {{2021}}, } @article{11950, abstract = {{Advances in electromyographic (EMG) sensor technology and machine learning algorithms have led to an increased research effort into high density EMG-based pattern recognition methods for prosthesis control. With the goal set on an autonomous multi-movement prosthesis capable of performing training and classification of an amputee’s EMG signals, the focus of this paper lies in the acceleration of the embedded signal processing chain. We present two Xilinx Zynq-based architectures for accelerating two inherently different high density EMG-based control algorithms. The first hardware accelerated design achieves speed-ups of up to 4.8 over the software-only solution, allowing for a processing delay lower than the sample period of 1 ms. The second system achieved a speed-up of 5.5 over the software-only version and operates at a still satisfactory low processing delay of up to 15 ms while providing a higher reliability and robustness against electrode shift and noisy channels.}}, author = {{Boschmann, Alexander and Agne, Andreas and Thombansen, Georg and Witschen, Linus Matthias and Kraus, Florian and Platzner, Marco}}, issn = {{0743-7315}}, journal = {{Journal of Parallel and Distributed Computing}}, keywords = {{High density electromyography, FPGA acceleration, Medical signal processing, Pattern recognition, Prosthetics}}, pages = {{77--89}}, publisher = {{Elsevier}}, title = {{{Zynq-based acceleration of robust high density myoelectric signal processing}}}, doi = {{10.1016/j.jpdc.2018.07.004}}, volume = {{123}}, year = {{2019}}, } @article{41866, author = {{Russer, Johannes A. and Uddin, Nasir and Awny, Ahmed Sanaa and Thiede, Andreas and Russer, Peter}}, issn = {{2162-2264}}, journal = {{IEEE Electromagnetic Compatibility Magazine}}, keywords = {{Electrical and Electronic Engineering, Computer Networks and Communications, Instrumentation, Signal Processing, Software}}, number = {{3}}, pages = {{79--85}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{Near-field measurement of stochastic electromagnetic fields}}}, doi = {{10.1109/memc.2015.7336761}}, volume = {{4}}, year = {{2015}}, } @article{39479, author = {{Vidor, Fábio and Meyers, Thorsten and Hilleringmann, Ulrich}}, issn = {{2079-9292}}, journal = {{Electronics}}, keywords = {{Electrical and Electronic Engineering, Computer Networks and Communications, Hardware and Architecture, Signal Processing, Control and Systems Engineering}}, number = {{3}}, pages = {{480--506}}, publisher = {{MDPI AG}}, title = {{{Flexible Electronics: Integration Processes for Organic and Inorganic Semiconductor-Based Thin-Film Transistors}}}, doi = {{10.3390/electronics4030480}}, volume = {{4}}, year = {{2015}}, } @article{11850, abstract = {{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.}}, author = {{Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{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}}, number = {{1}}, pages = {{206--219}}, title = {{{Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation}}}, doi = {{10.1109/TASL.2010.2047324}}, volume = {{19}}, year = {{2011}}, } @inproceedings{11913, abstract = {{In this paper we propose to employ directional statistics in a complex vector space to approach the problem of blind speech separation in the presence of spatially correlated noise. We interpret the values of the short time Fourier transform of the microphone signals to be draws from a mixture of complex Watson distributions, a probabilistic model which naturally accounts for spatial aliasing. The parameters of the density are related to the a priori source probabilities, the power of the sources and the transfer function ratios from sources to sensors. Estimation formulas are derived for these parameters by employing the Expectation Maximization (EM) algorithm. The E-step corresponds to the estimation of the source presence probabilities for each time-frequency bin, while the M-step leads to a maximum signal-to-noise ratio (MaxSNR) beamformer in the presence of uncertainty about the source activity. Experimental results are reported for an implementation in a generalized sidelobe canceller (GSC) like spatial beamforming configuration for 3 speech sources with significant coherent noise in reverberant environments, demonstrating the usefulness of the novel modeling framework.}}, author = {{Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)}}, keywords = {{array signal processing, blind source separation, blind speech separation, complex vector space, complex Watson distribution, directional statistics, expectation-maximisation algorithm, expectation maximization algorithm, Fourier transform, Fourier transforms, generalized sidelobe canceller, interference suppression, maximum signal-to-noise ratio beamformer, microphone signal, probabilistic model, spatial aliasing, spatial beamforming configuration, speech enhancement, statistical distributions}}, pages = {{241--244}}, title = {{{Blind speech separation employing directional statistics in an Expectation Maximization framework}}}, doi = {{10.1109/ICASSP.2010.5495994}}, year = {{2010}}, } @inproceedings{17253, author = {{Vollmer, Anna-Lisa and Pitsch, Karola and Lohan, Katrin Solveig and Fritsch, Jannik and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{Development and Learning (ICDL), 2010 IEEE 9th International Conference on Development and Learning}}, keywords = {{tutoring interaction, social interaction, video signal processing, robot systems, paediatrics, neurophysiology, Learning, infant, feedback, biology computing, cognitive capabilities, cognition, children}}, pages = {{76--81}}, title = {{{Developing feedback: How children of different age contribute to a tutoring interaction with adults}}}, year = {{2010}}, } @inproceedings{11935, abstract = {{The generalized sidelobe canceller by Griffith and Jim is a robust beamforming method to enhance a desired (speech) signal in the presence of stationary noise. Its performance depends to a high degree on the construction of the blocking matrix which produces noise reference signals for the subsequent adaptive interference canceller. Especially in reverberated environments the beamformer may suffer from signal leakage and reduced noise suppression. In this paper a new blocking matrix is proposed. It is based on a generalized eigenvalue problem whose solution provides an indirect estimation of the transfer functions from the source to the sensors. The quality of the new generalized eigenvector blocking matrix is studied in simulated rooms with different reverberation times and is compared to alternatives proposed in the literature.}}, author = {{Warsitz, Ernst and Krueger, Alexander and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)}}, keywords = {{adaptive interference canceller, adaptive signal processing, array signal processing, beamforming method, eigenvalues and eigenfunctions, generalized eigenvector blocking matrix, generalized sidelobe canceller, interference suppression, matrix algebra, noise suppression, speech enhancement, transfer function estimation, transfer functions}}, pages = {{73--76}}, title = {{{Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller}}}, doi = {{10.1109/ICASSP.2008.4517549}}, year = {{2008}}, } @article{11927, abstract = {{Maximizing the output signal-to-noise ratio (SNR) of a sensor array in the presence of spatially colored noise leads to a generalized eigenvalue problem. While this approach has extensively been employed in narrowband (antenna) array beamforming, it is typically not used for broadband (microphone) array beamforming due to the uncontrolled amount of speech distortion introduced by a narrowband SNR criterion. In this paper, we show how the distortion of the desired signal can be controlled by a single-channel post-filter, resulting in a performance comparable to the generalized minimum variance distortionless response beamformer, where arbitrary transfer functions relate the source and the microphones. Results are given both for directional and diffuse noise. A novel gradient ascent adaptation algorithm is presented, and its good convergence properties are experimentally revealed by comparison with alternatives from the literature. A key feature of the proposed beamformer is that it operates blindly, i.e., it neither requires knowledge about the array geometry nor an explicit estimation of the transfer functions from source to sensors or the direction-of-arrival.}}, author = {{Warsitz, Ernst and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{acoustic signal processing, arbitrary transfer function, array signal processing, blind acoustic beamforming, direction-of-arrival, direction-of-arrival estimation, eigenvalues and eigenfunctions, generalized eigenvalue decomposition, gradient ascent adaptation algorithm, microphone arrays, microphones, narrowband array beamforming, sensor array, single-channel post-filter, spatially colored noise, transfer functions}}, number = {{5}}, pages = {{1529--1539}}, title = {{{Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition}}}, doi = {{10.1109/TASL.2007.898454}}, volume = {{15}}, year = {{2007}}, } @inproceedings{11930, abstract = {{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.}}, author = {{Warsitz, Ernst and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)}}, keywords = {{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}}, pages = {{iv/797--iv/800 Vol. 4}}, title = {{{Acoustic filter-and-sum beamforming by adaptive principal component analysis}}}, doi = {{10.1109/ICASSP.2005.1416129}}, volume = {{4}}, year = {{2005}}, } @inproceedings{11931, abstract = {{The paper is concerned with binaural signal processing for a bimodal human-robot interface with hearing and vision. The two microphone signals are processed to obtain an enhanced single-channel input signal for the subsequent speech recognizer and to localize the acoustic source, an important information for establishing a natural human-robot communication. We utilize a robust adaptive algorithm for filter-and-sum beamforming (FSB) and extract speaker direction information from the resulting FIR filter coefficients. Further, particle filtering is applied which conducts a nonlinear Bayesian tracking of speaker movement. Good location accuracy can be achieved even in highly reverberant environments. The results obtained outperform the conventional generalized cross correlation (GCC) method.}}, author = {{Warsitz, Ernst and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE Workshop on Multimedia Signal Processing (MMSP 2004)}}, keywords = {{bimodal human-robot interface, binaural signal processing, enhanced single-channel input signal, filter-and-sum beamforming, filtering theory, FIR filter coefficient, generalized cross correlation method, microphones, microphone signal, nonlinear Bayesian tracking, particle filtering, robust adaptive algorithm, robust speaker direction estimation, signal processing, speech enhancement, speech recognition, speech recognizer, user interfaces}}, pages = {{367--370}}, title = {{{Robust speaker direction estimation with particle filtering}}}, doi = {{10.1109/MMSP.2004.1436569}}, year = {{2004}}, }