Generalized Deflation Algorithms for the Blind Source-factor Separation of Mimo-fir Channels

The present paper proposes a class of iterative deflation algorithms to solve the blind source-factor separation for the outputs of multiple-input multiple-output finite impulse response (MIMO-FIR) channels. Using one of the proposed deflation algorithms, filtered versions of the source signals, each of which is the contribution of each source signal to the outputs of MIMO-FIR channels, are extracted one by one from the mixtures of source signals. The proposed deflation algorithms can be applied to various sources, that is, i.i.d. signals, second-order white but higher-order colored signals, and second-order correlated (non-white) signals, which are referred to as generalized deflation algorithms (GDA’s). The conventional deflation algorithms were proposed for each source signal mentioned above (e.g., [1, 5, 6, 8, 10]), that is, a class of deflation algorithms which can deal with each of the source signals mentioned above has not been proposed until now. Some simulation results are presented to show the validity of the proposed algorithms.