Natural gradient works efficiently in learning
Neural Computation
Evaluation of blind signal separation method using directivity pattern under reverberant conditions
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Blind source separation combining independent component analysis and beamforming
EURASIP Journal on Applied Signal Processing
Underdetermined convolutive blind source separation via time-frequency masking
IEEE Transactions on Audio, Speech, and Language Processing
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This paper addresses the well known permutation problem in frequency domain blind source separation. The proposed method uses correlation between two signals in each DFT bin to solve the permutation problem. One of the signals is partially separated by a time domain blind source separation method and the other is obtained by the frequency domain blind source separation method. Two different ways of configuring the time and frequency domain blocks, i.e., in parallel or cascade, have been studied. The cascaded configuration not only achieves a better separation performance but also reduces the computational cost as compared to the parallel configuration.