Single channel nonstationary signal separation using linear time-varying filters

James Hopgood, Peter J. W. Rayner

Research output: Contribution to journalArticlepeer-review

Abstract

Separability of signal mixtures given only one mixture observation is defined as the identification of the accuracy to which the signals can be separated. The paper shows that when signals are separated using the generalized Wiener filter, the degree of separability can be deduced from the signal structure. To identify this structure, the processes are represented on an general spectral domain, and a sufficient solution to the Wiener filter is obtained. The filter is composed of a term independent of the signal values, corresponding to regions in the spectral domain where the desired signal components are not distorted by interfering noise components, and a term dependent on the signal correlations, corresponding to the region where components overlap. An example of determining perfect separability of modulated random signals is given with application in radar and speech processing
Original languageEnglish
Pages (from-to)1739-1752
Number of pages14
JournalIEEE Transactions on Signal Processing
Volume51
Issue number7
DOIs
Publication statusPublished - 2003

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