ScholarLens Back to search
2003•Journal of Wuhan Yejin University of Science and TechnologyRequires access

Genetic Algorithm Approach to Blind Source Separation

Wei Yu

Open publisher page 1 citations

Abstract

Independent component analysis(ICA) is a new technique in signal processing .The goal of ICA is to find a separation matrix so that each component of the output signal obtained by transforming the observed multidimensional mixture of data is independent. A new genetic algorithm which combines GA with ICA for blind source separation is proposed in this paper. The convergence and stability of the algorithm are analysed and their validity is confirmed by the signal separation test.

About this research paper

What this paper is about

Independent component analysis(ICA) is a new technique in signal processing .The goal of ICA is to find a separation matrix so that each component of the output signal obtained by transforming the observed multidimensional mixture of data is independent. A new genetic algorithm which combines GA with ICA for blind source separation is proposed in this paper. The convergence and stability of the algorithm are analysed and their validity is confirmed by the signal separation test.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Independent component analysis(ICA) is a new technique in signal processing .The goal of ICA is to find a separation matrix so that each component of the output signal obtained by transforming the observed multidimensional mixture of data is independent. A new genetic algorithm which combines GA with ICA for blind source separation is proposed in this paper. The convergence and stability of the algorithm are analysed and their validity is confirmed by the signal separation test.

Key concepts: Independent component analysis, Blind signal separation, SIGNAL (programming language), Convergence (economics), Algorithm, Stability (learning theory), Separation (statistics), Computer science

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
Genetic Algorithm Approach to Blind Source Separation — Research Paper | ScholarLens