A genetic algorithm for blind source separation based on independent component analysis

This paper presents the implementation of genetic algorithm (GA) to a simple blind source separation(BSS) problem using independent component analysis(ICA). The process did not include pre-processing of mixture signals such as centering and whitening like most of ICA algorithms. The GA directly gues...

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Main Authors: Dadula, Cristina P., Dadios, Elmer P.
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Published: Animo Repository 2014
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/2342
https://animorepository.dlsu.edu.ph/context/faculty_research/article/3341/type/native/viewcontent
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-33412021-08-24T08:09:03Z A genetic algorithm for blind source separation based on independent component analysis Dadula, Cristina P. Dadios, Elmer P. This paper presents the implementation of genetic algorithm (GA) to a simple blind source separation(BSS) problem using independent component analysis(ICA). The process did not include pre-processing of mixture signals such as centering and whitening like most of ICA algorithms. The GA directly guesses the coefficients of the separating matrix given the mixture signals as inputs using maximization of kurtosis and minimization of mutual information as fitness function. Only one fitness function was defined to account the fitness for kurtosis and mutual information. Three set of simulations were performed. The first two simulations used the mixture of two and three synthetic signals, respectively. The third simulation used four audio signals. The results show that the proposed algorithm indeed separates the independent sources consisting of synthetic signals. The simulation consisting of four audio signals separates only three signals. It failed to extract one signal probably because the signal is almost a gaussian signal. © 2014 IEEE. 2014-01-01T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/2342 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3341/type/native/viewcontent Faculty Research Work Animo Repository Genetic algorithms Blind source separation independent component analysis Electrical and Computer Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Genetic algorithms
Blind source separation
independent component analysis
Electrical and Computer Engineering
spellingShingle Genetic algorithms
Blind source separation
independent component analysis
Electrical and Computer Engineering
Dadula, Cristina P.
Dadios, Elmer P.
A genetic algorithm for blind source separation based on independent component analysis
description This paper presents the implementation of genetic algorithm (GA) to a simple blind source separation(BSS) problem using independent component analysis(ICA). The process did not include pre-processing of mixture signals such as centering and whitening like most of ICA algorithms. The GA directly guesses the coefficients of the separating matrix given the mixture signals as inputs using maximization of kurtosis and minimization of mutual information as fitness function. Only one fitness function was defined to account the fitness for kurtosis and mutual information. Three set of simulations were performed. The first two simulations used the mixture of two and three synthetic signals, respectively. The third simulation used four audio signals. The results show that the proposed algorithm indeed separates the independent sources consisting of synthetic signals. The simulation consisting of four audio signals separates only three signals. It failed to extract one signal probably because the signal is almost a gaussian signal. © 2014 IEEE.
format text
author Dadula, Cristina P.
Dadios, Elmer P.
author_facet Dadula, Cristina P.
Dadios, Elmer P.
author_sort Dadula, Cristina P.
title A genetic algorithm for blind source separation based on independent component analysis
title_short A genetic algorithm for blind source separation based on independent component analysis
title_full A genetic algorithm for blind source separation based on independent component analysis
title_fullStr A genetic algorithm for blind source separation based on independent component analysis
title_full_unstemmed A genetic algorithm for blind source separation based on independent component analysis
title_sort genetic algorithm for blind source separation based on independent component analysis
publisher Animo Repository
publishDate 2014
url https://animorepository.dlsu.edu.ph/faculty_research/2342
https://animorepository.dlsu.edu.ph/context/faculty_research/article/3341/type/native/viewcontent
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