Separation of periodically time-varying mixtures using second-order statistics

Tzahi Weisman, Arie Yeredor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We address the problem of Blind Source Separation (BSS) in the context of instantaneous (memoryless) linear mixtures, where the unknown mixing coefficients are time varying, changing periodically in time. Such a mixing model is realistic, e.g., when considering a biological or physiological system where the mixing coefficients are affected by periodic processes like breathing, heart-beating etc. Assuming stationary sources with distinct spectra, we rely on second-order statistics (SOS) and offer an expansion of the classical Second Order Blind Identification (SOBI) algorithm, accommodating the periodic variation model. The proposed algorithm consists of estimating several types of correlation matrices related to the time-varying SOS of the observations, followed by applying generalized joint diagonalization, which leads to estimates of the parameters of the periodic mixing. These estimated parameters are used in turn to apply a time-vary ing unmixing operation, recovering the desired sources. In its basic form (as presented in here), the algorithm requires prior knowledge (or a good estimate) of the cyclic period. We demonstrate the performance improvement over SOBI in simulation.

Original languageEnglish
Title of host publicationIndependent Component Analysis and Blind Signal Separation - 6th International Conference, ICA 2006, Proceedings
Pages278-285
Number of pages8
DOIs
StatePublished - 2006
Event6th International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2006 - Charleston, SC, United States
Duration: 5 Mar 20068 Mar 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3889 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Independent Component Analysis and Blind Signal Separation, ICA 2006
Country/TerritoryUnited States
CityCharleston, SC
Period5/03/068/03/06

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