Title :
Multi-channel signal separation based on cross-bispectra
Author :
Yellin, Daniel ; Weinstein, Ehud
Author_Institution :
Dept. of Electr. Eng.-Syst., Tel-Aviv Univ., Ramat-Aviv, Israel
Abstract :
The authors consider the problem in which they want to separate two (or more) signals that are coupled to each other through an unknown multiple-input-multiple-output linear time invariant system. They prove that the signals can be decoupled, or separated, using only the condition that they are statistically independent, and find even weaker sufficient conditions involving their cross-bispectra. By imposing these conditions on the reconstructed signals, they obtain a criterion for signal separation. A computationally efficient iterative algorithm for solving the proposed criterion, that only involves the iterative solution to a linear least squares problem, is presented.
Keywords :
iterative methods; least squares approximations; linear systems; spectral analysis; MIMO; cross-bispectra; iterative algorithm; iterative solution; linear least squares; linear time invariant system; multichannel signal separation; multiple-input-multiple-output; reconstructed signals; sufficient conditions; Filters; Frequency response; Interference; Iterative algorithms; Least squares methods; Signal processing; Source separation; Sufficient conditions; Systems engineering and theory; Time invariant systems;
Conference_Titel :
Higher-Order Statistics, 1993., IEEE Signal Processing Workshop on
Conference_Location :
South Lake Tahoe, CA, USA
Print_ISBN :
0-7803-1238-4
DOI :
10.1109/HOST.1993.264553