A novel algorithm for independent component analysis with reference and methods for its applications.

This paper presents a stable and fast algorithm for independent component analysis with reference (ICA-R). This is a technique for incorporating available reference signals into the ICA contrast function so as to form an augmented Lagrangian function under the framework of constrained ICA (cICA). Th...

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Autor principal:	Jian-Xun Mi
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b32bdff2bd8d48179a9aefc925eeaa37
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id	oai:doaj.org-article:b32bdff2bd8d48179a9aefc925eeaa37
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spelling	oai:doaj.org-article:b32bdff2bd8d48179a9aefc925eeaa372021-11-18T08:19:26ZA novel algorithm for independent component analysis with reference and methods for its applications.1932-620310.1371/journal.pone.0093984https://doaj.org/article/b32bdff2bd8d48179a9aefc925eeaa372014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24826986/?tool=EBIhttps://doaj.org/toc/1932-6203This paper presents a stable and fast algorithm for independent component analysis with reference (ICA-R). This is a technique for incorporating available reference signals into the ICA contrast function so as to form an augmented Lagrangian function under the framework of constrained ICA (cICA). The previous ICA-R algorithm was constructed by solving the optimization problem via a Newton-like learning style. Unfortunately, the slow convergence and potential misconvergence limit the capability of ICA-R. This paper first investigates and probes the flaws of the previous algorithm and then introduces a new stable algorithm with a faster convergence speed. There are two other highlights in this paper: first, new approaches, including the reference deflation technique and a direct way of obtaining references, are introduced to facilitate the application of ICA-R; second, a new method is proposed that the new ICA-R is used to recover the complete underlying sources with new advantages compared with other classical ICA methods. Finally, the experiments on both synthetic and real-world data verify the better performance of the new algorithm over both previous ICA-R and other well-known methods.Jian-Xun MiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 5, p e93984 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jian-Xun Mi A novel algorithm for independent component analysis with reference and methods for its applications.
description	This paper presents a stable and fast algorithm for independent component analysis with reference (ICA-R). This is a technique for incorporating available reference signals into the ICA contrast function so as to form an augmented Lagrangian function under the framework of constrained ICA (cICA). The previous ICA-R algorithm was constructed by solving the optimization problem via a Newton-like learning style. Unfortunately, the slow convergence and potential misconvergence limit the capability of ICA-R. This paper first investigates and probes the flaws of the previous algorithm and then introduces a new stable algorithm with a faster convergence speed. There are two other highlights in this paper: first, new approaches, including the reference deflation technique and a direct way of obtaining references, are introduced to facilitate the application of ICA-R; second, a new method is proposed that the new ICA-R is used to recover the complete underlying sources with new advantages compared with other classical ICA methods. Finally, the experiments on both synthetic and real-world data verify the better performance of the new algorithm over both previous ICA-R and other well-known methods.
format	article
author	Jian-Xun Mi
author_facet	Jian-Xun Mi
author_sort	Jian-Xun Mi
title	A novel algorithm for independent component analysis with reference and methods for its applications.
title_short	A novel algorithm for independent component analysis with reference and methods for its applications.
title_full	A novel algorithm for independent component analysis with reference and methods for its applications.
title_fullStr	A novel algorithm for independent component analysis with reference and methods for its applications.
title_full_unstemmed	A novel algorithm for independent component analysis with reference and methods for its applications.
title_sort	novel algorithm for independent component analysis with reference and methods for its applications.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/b32bdff2bd8d48179a9aefc925eeaa37
work_keys_str_mv	AT jianxunmi anovelalgorithmforindependentcomponentanalysiswithreferenceandmethodsforitsapplications AT jianxunmi novelalgorithmforindependentcomponentanalysiswithreferenceandmethodsforitsapplications
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A novel algorithm for independent component analysis with reference and methods for its applications.

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