Fuzzy channel-optimized vector quantization

Wen-Jyi Hwang, Faa Jeng Lin, Chin Tsai Lin

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A novel fuzzy clustering algorithm for the design of channel-optimized source coding systems is presented in this letter. The algorithm, termed fuzzy channel-optimized vector quantizer (FCOVQ) design algorithm, optimizes the vector quantizer (VQ) design using a fuzzy clustering process in which the index crossover probabilities imposed by a noisy channel are taken into account. The fuzzy clustering process effectively enhances the robustness of the performance of VQ to channel noise without reducing the quantization accuracy. Numerical results demonstrate that the FCOVQ algorithm outperforms existing VQ algorithms under noisy channel conditions for both Gauss-Markov sources and still image data.

Original languageEnglish
Pages (from-to)408-410
Number of pages3
JournalIEEE Communications Letters
Volume4
Issue number12
DOIs
Publication statusPublished - 2000 Jan 1

Fingerprint

Vector Quantization
Vector quantization
Fuzzy clustering
Fuzzy Clustering
Fuzzy Algorithm
Channel Coding
Source Coding
Algorithm Design
Clustering algorithms
Gauss
Clustering Algorithm
Crossover
Quantization
Optimise
Robustness
Numerical Results
Demonstrate
Design

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Fuzzy channel-optimized vector quantization. / Hwang, Wen-Jyi; Lin, Faa Jeng; Lin, Chin Tsai.

In: IEEE Communications Letters, Vol. 4, No. 12, 01.01.2000, p. 408-410.

Research output: Contribution to journalArticle

Hwang, Wen-Jyi ; Lin, Faa Jeng ; Lin, Chin Tsai. / Fuzzy channel-optimized vector quantization. In: IEEE Communications Letters. 2000 ; Vol. 4, No. 12. pp. 408-410.
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