Local stability analysis of flexible independent component analysis algorithm

Seungjin Choi, Andrzej Cichocki, Shunichi Amari

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

6 Scopus citations

Abstract

This paper addresses local stability analysis for the flexible independent component analysis (ICA) algorithm where the generalized Gaussian density model was employed for blind separation of mixtures of sub- and super-Gaussian sources. In the flexible ICA algorithm, the shape of nonlinear function in the learning algorithm varies depending on the Gaussian exponent which is properly selected according to the kurtosis of estimated source. In the framework of the natural gradient in Stiefel manifold, the flexible ICA algorithm is revisited and some new results about its local stability analysis are presented.

Original languageEnglish
Title of host publicationDesign and Implementation of Signal Processing SystemNeural Networks for Signal Processing Signal Processing EducationOther Emerging Applications of Signal ProcessingSpecial Sessions
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3426-3429
Number of pages4
ISBN (Electronic)0780362934
DOIs
StatePublished - 2000
Externally publishedYes
Event25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey
Duration: 5 Jun 20009 Jun 2000

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume6
ISSN (Print)1520-6149

Conference

Conference25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000
Country/TerritoryTurkey
CityIstanbul
Period5/06/009/06/00

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