A sequential approach to sparse component analysis

Authors

Daniel Smith, University of WollongongFollow
Jason Lukasiak, University of WollongongFollow
I. Burnett, University of WollongongFollow

RIS ID

12938

Publication Details

This paper was originally published as: Smith, D, Lukasiak, J & Burnett, I, A sequential approach to sparse component analysis, 2005 IEEE 7th Workshop on Multimedia Signal Processing (MMSP-05), Shanghai, China, 30 October-2 November 2005, 1-4. Copyright IEEE 2005.

Abstract

A sequential approach to sparse component analysis (SeqTIF) is proposed in this paper. Although SeqTIF employs the estimation process of the simultaneous TIFROM algorithm, a source cancellation and deflation technique are also incorporated to sequentially estimate speech signals in the mixture. Results indicate that SeqTIF's separation performance shows a clear improvement upon the simultaneous TIFROM approach, due to the less restrictive assumptions it places upon the signals in the mixture. In particular, the analysis indicates SeqTIF's data efficiency is high, enabling the sequential approach to track a time-varying mixture with much greater accuracy than the simultaneous algorithm. Furthermore, SeqTIF is a more flexible approach, free from the constraints that a simultaneous approach places upon the mixing system.