Blind separation of convolutive mixtures
José Carlos Príncipe, Hsiao‐Chun Wu · 2003
Reverberant signals recorded by multiple microphones can be described as sums of sources convolved with different parameters. Blind source separation of this unknown linear system can be transformed to a set of instantaneous mixtures for every frequency band. In each frequency band, we may use the simultaneous diagonalization algorithms to separate the sources. In addition to our previous simultaneous diagonalization to minimize the Frobenius norm, we now propose another set of efficient simultaneous diagonalization algorithms based on Hadamard's inequality to make the source separation feasible in the frequency domain.