System identification
A neural net for blind separation of nonstationary signals
Neural Networks
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Neural Networks for Optimization and Signal Processing
Neural Networks for Optimization and Signal Processing
Linear Prediction of Speech
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Topographic Independent Component Analysis
Neural Computation
The generalized multidelay adaptive filter: structure andconvergence analysis
IEEE Transactions on Signal Processing
EVAM: an eigenvector-based algorithm for multichannel blinddeconvolution of input colored signals
IEEE Transactions on Signal Processing
Exploiting narrowband efficiency for broadband convolutive blind source separation
EURASIP Journal on Applied Signal Processing
Combination of adaptive feedback cancellation and binaural adaptive filtering in hearing aids
EURASIP Journal on Advances in Signal Processing - Special issue on digital signal processing for hearing instruments
A novel blind source separation method for single-channel signal
Signal Processing
EURASIP Journal on Audio, Speech, and Music Processing - Special issue on environmental sound synthesis, processing, and retrieval
A novel normalization and regularization scheme for broadband convolutive blind source separation
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Modulation domain blind speech separation in noisy environments
Speech Communication
Generalized Spherical Array Beamforming for Binaural Speech Reproduction
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
| Hi-index | 0.08 |
In this paper, we present an efficient real-time implementation of a broadband algorithm for blind source separation (BSS) of convolutive mixtures. A recently introduced generic BSS framework based on a matrix formulation allows simultaneous exploitation of nonwhiteness and nonstationarity of the source signals using second-order statistics. We demonstrate here that this general scheme leads to highly efficient real-time algorithms based on block-online adaptation suitable for ordinary PC platforms. Moreover, we investigate the problem of incorporating noncausal delays which are necessary with certain geometric constellations. Furthermore, the robustness against diffuse background noise, eg., in a car environment is examined and a stepsize control is proposed which further enhances the robustness in real-world environments and leads to an improvement in separation performance. The algorithms were investigated in a reverberant office room and in noisy car environments verifying that the proposed method ensures high separation performance in realistic scenarios.