Hybrid genetic algorithm for design of robust communication systems

Chien Min Ou; Jing Jhih Chen; Wen Jyi Hwang

doi:10.4304/jsw.1.3.24-31

Hybrid genetic algorithm for design of robust communication systems

Chien Min Ou, Jing Jhih Chen, Wen Jyi Hwang

Department of Computer Science and Information Engineering

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

A novel hybrid genetic algorithm (GA) for jointly optimizing source and channel codes is presented in this paper. The algorithm first uses GA for the coarse search of source and channel codes. An iterative search is then followed for the refinement of the coarse search. The hybrid GA enhances the robustness of the design of source and channel codes. The distributed GA scheme can also be used in conjunction with the proposed hybrid GA algorithm for further performance improvement.

Original language	English
Pages (from-to)	24-31
Number of pages	8
Journal	Journal of Software
Volume	1
Issue number	3
DOIs	https://doi.org/10.4304/jsw.1.3.24-31
Publication status	Published - 2006 Sep

Keywords

Error correct coding
Genetic algorithm
Vector quantization

ASJC Scopus subject areas

Software
Human-Computer Interaction
Artificial Intelligence

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author = "Ou, {Chien Min} and Chen, {Jing Jhih} and Hwang, {Wen Jyi}",

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KW - Error correct coding

KW - Genetic algorithm

KW - Vector quantization

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Hybrid genetic algorithm for design of robust communication systems

Abstract

Keywords

ASJC Scopus subject areas

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