A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices

This paper proposes a new algorithm to improve robustness, reliability and efficiency for blind signal separation with a different diagonal cumulant maximization criterion. It calculates a fraction of the fourth order cumulant set and avoids the eigenmatrix decomposition to considerably reduce the s...

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Main Authors: Liu, Xianhua, Randall, R.
Other Authors: Hans-A. Bachor
Format: Conference Paper
Published: Australian Institute of Physics 2005
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/5080
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author Liu, Xianhua
Randall, R.
author2 Hans-A. Bachor
author_facet Hans-A. Bachor
Liu, Xianhua
Randall, R.
author_sort Liu, Xianhua
building Curtin Institutional Repository
collection Online Access
description This paper proposes a new algorithm to improve robustness, reliability and efficiency for blind signal separation with a different diagonal cumulant maximization criterion. It calculates a fraction of the fourth order cumulant set and avoids the eigenmatrix decomposition to considerably reduce the separation cost for large-scale problems. Experimental separation shows that the new algorithm is robust, reliable and efficient for both large and small-scale separation problems, thus has combined merits of the well-known JADE and Fast ICA algorithms. Mixed music and speech signal separation is presented in this paper.
first_indexed 2025-11-14T06:05:34Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T06:05:34Z
publishDate 2005
publisher Australian Institute of Physics
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-50802022-10-11T07:36:51Z A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices Liu, Xianhua Randall, R. Hans-A. Bachor Massimiliano Colla Independent component analysis Blind source separation fourth order cumulant matrix diagonalization This paper proposes a new algorithm to improve robustness, reliability and efficiency for blind signal separation with a different diagonal cumulant maximization criterion. It calculates a fraction of the fourth order cumulant set and avoids the eigenmatrix decomposition to considerably reduce the separation cost for large-scale problems. Experimental separation shows that the new algorithm is robust, reliable and efficient for both large and small-scale separation problems, thus has combined merits of the well-known JADE and Fast ICA algorithms. Mixed music and speech signal separation is presented in this paper. 2005 Conference Paper http://hdl.handle.net/20.500.11937/5080 Australian Institute of Physics restricted
spellingShingle Independent component analysis
Blind source separation
fourth order cumulant matrix
diagonalization
Liu, Xianhua
Randall, R.
A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices
title A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices
title_full A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices
title_fullStr A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices
title_full_unstemmed A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices
title_short A new independent component analysis algorithm: Joint approximate diagonalization of simplified cumulant matrices
title_sort new independent component analysis algorithm: joint approximate diagonalization of simplified cumulant matrices
topic Independent component analysis
Blind source separation
fourth order cumulant matrix
diagonalization
url http://hdl.handle.net/20.500.11937/5080