A data processing system blind source separation of an overcomplete set of signals generally includes means for storing input from sensors in a mixed signal matrix X 200, noise in a noise matrix V 202, an estimate of the individual signals from the mixture of signals from the signal sources in a source signal estimate matrix S 204, and an estimate of environmental effects in a mixing matrix A 206, the matrices related by X=AS+V; generating an initial estimate of A 208; determining the number of, and associated lines of correlation of, each source from A, and representing the sources in the source signal estimate matrix S 210; jointly optimizing S and A in an iterative manner to generate an optimized source signal estimate matrix S 212 and a final estimated mixing matrix A; and restoring the separated source signals from the optimized source signal estimate matrix S 214.
PRIORITY CLAIM
This application claims the benefit of priority to provisional applications No. 60/246,498, filed in the United States on Nov. 9, 2000, and titled "Over-complete bss by applying sparse decomposition and information theoretic based probabilistic approach".
A system and method for non-square blind source separation (BSS) under coherent noise. The system and method for non-square BSS estimates the mixing parameters of a mixed source signal and filters the estimated mixing parameters so that output noise is reduced and the mixed source signal is separated from the noise. The filtering is accomplished by a linear filter that performs a beamforming for reducing the noise and another linear filter that solves a source separation problem by selecting time-frequency points where, according to a W-disjoint orthogonality assumption, only one source is active.
A communications device includes an antenna array for receiving different summations of source signals from a plurality of signal sources, a receiver coupled to the antenna array for receiving the different summations of source signals, and a signal separation processor coupled to the receiver. Processing by the signal separation processor includes creating a matrix based upon the different summations of source signals, with the matrix being defined by linear independent equations with fewer equations than unknowns. The matrix is underdetermined, and parameters associated with the matrix are modified based upon different sets of parameter values, and respective matrix quality factors associated with the different sets of parameter values are determined. The matrix is then biased with a preferred set of parameter values so that the solution space may be narrowed for obtaining a solution.
