Generalized Cauchy Distribution (GCD)-based score functions for a fast and flexible subband decomposition ICA

Marko Kanadi, Muhammad Tahir Akhtar, Wataru Mitsuhashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a new score function for subband decomposition ICA to improve the algorithm performance. Subband decomposition ICA is known to having better separation performance than frequency-domain ICA. However, it is basically time-domain ICA, with much shorter filters, performed on each subband. In this paper, discussion is focused on an information-maximization based approach which performance depends on the distribution assumption of source signals. We propose the use of a generalized Cauchy distribution as a new distribution assumption to derive a new score function. With the proposed score-function, the performance of subband decomposition ICA algorithm is significantly improved in terms of both SIR and convergence speed.

Original languageEnglish
Title of host publication4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings
DOIs
Publication statusPublished - Dec 1 2010
Event4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Gold Coast, QLD, Australia
Duration: Dec 13 2010Dec 15 2010

Publication series

Name4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings

Conference

Conference4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010
CountryAustralia
CityGold Coast, QLD
Period12/13/1012/15/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

Fingerprint Dive into the research topics of 'Generalized Cauchy Distribution (GCD)-based score functions for a fast and flexible subband decomposition ICA'. Together they form a unique fingerprint.

Cite this