Convergence of blind delayed source separation algorithms, which use constant learning rates, is known to be slow. We propose a fuzzy logic based approach to adaptively select the learning rates, for estimates of delays and cross-weights, in the blind delayed source separation algorithm. We make use of the state of independence of the separated outputs. We also propose a performance index to me...

As statistical independence exists between marine mammals sound and watercraft emitted noise and among different organism signals, the study introduces blind source separation into marine mammal signals processing. Blind source separation with single hydrophone is a special underdetermined blind separation problem and blind source separation based on matrix calculating is no longer suitable. Th...

This thesis addresses the problem of blind signal separation (BSS) using independent component analysis (ICA). In blind signal separation, signals from multiple sources arrive simultaneously at a sensor array, so that each sensor array output contains a mixture of source signals. Sets of sensor outputs are processed to recover the source signals or to identify the mixing system. The term blind ...

7 This paper addresses the well known permutation problem in frequency domain 8 blind source separation. The proposed method uses correlation between two signals 9 in each DFT bin to solve the permutation problem. One of the signals is par10 tially separated by a time domain blind source separation method and the other 11 is obtained by the frequency domain blind source separation method. Two d...