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

Fingerprint

Communication

Keywords

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

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

Cite this

Genetic channel-optimized vector quantizer design for burst error channels. / Hwang, Wen-Jyi; Ou, Chien Min; Yeh, Chin Ming.

In: Neurocomputing, Vol. 63, No. SPEC. ISS., 01.01.2005, p. 345-357.

Research output: Contribution to journalArticle

Hwang, Wen-Jyi ; Ou, Chien Min ; Yeh, Chin Ming. / Genetic channel-optimized vector quantizer design for burst error channels. In: Neurocomputing. 2005 ; Vol. 63, No. SPEC. ISS. pp. 345-357.
@article{2b8ded9006ac48838d5bac2ff47cb838,
title = "Genetic channel-optimized vector quantizer design for burst error channels",
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.",
keywords = "Channel-optimized source coding, Genetic algorithm, Vector quantization",
author = "Wen-Jyi Hwang and Ou, {Chien Min} and Yeh, {Chin Ming}",
year = "2005",
month = "1",
day = "1",
doi = "10.1016/j.neucom.2004.04.014",
language = "English",
volume = "63",
pages = "345--357",
journal = "Neurocomputing",
issn = "0925-2312",
publisher = "Elsevier",
number = "SPEC. ISS.",

}

TY - JOUR

T1 - Genetic channel-optimized vector quantizer design for burst error channels

AU - Hwang, Wen-Jyi

AU - Ou, Chien Min

AU - Yeh, Chin Ming

PY - 2005/1/1

Y1 - 2005/1/1

N2 - 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.

AB - 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.

KW - Channel-optimized source coding

KW - Genetic algorithm

KW - Vector quantization

UR - http://www.scopus.com/inward/record.url?scp=12144251074&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=12144251074&partnerID=8YFLogxK

U2 - 10.1016/j.neucom.2004.04.014

DO - 10.1016/j.neucom.2004.04.014

M3 - Article

AN - SCOPUS:12144251074

VL - 63

SP - 345

EP - 357

JO - Neurocomputing

JF - Neurocomputing

SN - 0925-2312

IS - SPEC. ISS.

ER -