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DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Blind separation of piecewise stationary non-Gaussian sources
Signal Processing
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Underdetermined convolutive blind source separation via time-frequency masking
IEEE Transactions on Audio, Speech, and Language Processing
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Correlation-based amplitude estimation of coincident partials in monaural musical signals
EURASIP Journal on Audio, Speech, and Music Processing
EURASIP Journal on Audio, Speech, and Music Processing - Special issue on environmental sound synthesis, processing, and retrieval
A multistage approach to blind separation of convolutive speech mixtures
Speech Communication
Expert Systems with Applications: An International Journal
Stability of independent vector analysis
Signal Processing
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This paper derives two spatio-temporal extensions of the well-known FastICA algorithm of Hyvarinen and Oja that are applicable to the convolutive blind source separation task. Our time-domain algorithms combine multichannel spatio-temporal prewhitening via multistage least-squares linear prediction with novel adaptive procedures that impose paraunitary constraints on the multichannel separation filter. The techniques converge quickly to a separation solution without any step size selection or divergence difficulties, and unlike other methods, ours do not require special coefficient initialization procedures to obtain good separation performance. They also allow for the efficient reconstruction of individual signals as observed in the sensor measurements directly from the system parameters for single-input multiple-output blind source separation tasks. An analysis of one of the adaptive constraint procedures shows its fast convergence to a paraunitary filter bank solution. Numerical evaluations of the proposed algorithms and comparisons with several existing convolutive blind source separation techniques indicate the excellent relative performance of the proposed methods.