Cover Image

A review of independent component analysis (ICA) based on Kurtosis Contrast Function

Independent component analysis (ICA) is a computational mehtod to solve blind source separation (BSS) problem. Different kinds of classic measure can be used for the estimation of nonGaussian sources by ICA. In this paper we review independent componenet analysis (ICA) technique based on Kurtosis co...

Full description

Saved in:
Bibliographic Details
Main Authors: Ahmad, Tahir, Ghanbari, Mahdi
Format: Article
Published: INSInet Publications 2011
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/44703/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.44703
record_format eprints
spelling my.utm.447032017-08-30T03:06:14Z http://eprints.utm.my/id/eprint/44703/ A review of independent component analysis (ICA) based on Kurtosis Contrast Function Ahmad, Tahir Ghanbari, Mahdi QA Mathematics Independent component analysis (ICA) is a computational mehtod to solve blind source separation (BSS) problem. Different kinds of classic measure can be used for the estimation of nonGaussian sources by ICA. In this paper we review independent componenet analysis (ICA) technique based on Kurtosis contrast function. We briefly present the common independent component analysis algorithms that use Kurtosis as a criterion for non-Gaussian. Basid on the literatures, we compare these algrithms in terms of performance and advantaves. INSInet Publications 2011 Article PeerReviewed Ahmad, Tahir and Ghanbari, Mahdi (2011) A review of independent component analysis (ICA) based on Kurtosis Contrast Function. Australian Journal of Basic and Applied Sciences, 5 (9). pp. 1747-1755. ISSN 1991-8178
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Ahmad, Tahir
Ghanbari, Mahdi
A review of independent component analysis (ICA) based on Kurtosis Contrast Function
description Independent component analysis (ICA) is a computational mehtod to solve blind source separation (BSS) problem. Different kinds of classic measure can be used for the estimation of nonGaussian sources by ICA. In this paper we review independent componenet analysis (ICA) technique based on Kurtosis contrast function. We briefly present the common independent component analysis algorithms that use Kurtosis as a criterion for non-Gaussian. Basid on the literatures, we compare these algrithms in terms of performance and advantaves.
format Article
author Ahmad, Tahir
Ghanbari, Mahdi
author_facet Ahmad, Tahir
Ghanbari, Mahdi
author_sort Ahmad, Tahir
title A review of independent component analysis (ICA) based on Kurtosis Contrast Function
title_short A review of independent component analysis (ICA) based on Kurtosis Contrast Function
title_full A review of independent component analysis (ICA) based on Kurtosis Contrast Function
title_fullStr A review of independent component analysis (ICA) based on Kurtosis Contrast Function
title_full_unstemmed A review of independent component analysis (ICA) based on Kurtosis Contrast Function
title_sort review of independent component analysis (ica) based on kurtosis contrast function
publisher INSInet Publications
publishDate 2011
url http://eprints.utm.my/id/eprint/44703/
_version_ 1643651518622072832
score 13.160551

Similar Items