Genetic channel-optimized vector quantizer design for burst error channels

Wen-Jyi Hwang, Chien Min Ou, Chin Ming Yeh

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents a novel vector quantizer (VQ) design algorithm optimized to a burst error channel (BEC) for robust communication. The Gilbert-Elliot model is used to describe the BEC. Based on the model, the objective of this algorithm is to minimize the average distortion when the BEC is in the normal state of operation, while maintaining a minimum fidelity when the BEC is in the undesirable state. In the algorithm, an iterative design procedure is first derived for obtaining a local optimal solution to the problem. A novel genetic scheme is then proposed for attaining a near global optimal performance. Numerical results show that, when delivering information over the BEC, the algorithm significantly outperforms the VQ techniques optimizing the design only to the simple binary symmetric channels.

Original languageEnglish
Pages (from-to)345-357
Number of pages13
JournalNeurocomputing
Volume63
Issue numberSPEC. ISS.
DOIs
Publication statusPublished - 2005 Jan 1

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Keywords

  • Channel-optimized source coding
  • Genetic algorithm
  • Vector quantization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

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