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Design of Robust Communication Systems Using Genetic Algorithms

  • Chien-Min Ou
  • Wen-Jyi Hwang
  • Hung-Chuan Yung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3905)

Abstract

This paper presents a novel genetic algorithm for jointly optimizing source and channel codes. The algorithm uses a channel-optimized vector quantizer for the source code, and a rate-punctured convolutional code for the channel code. The genetic algorithm enhances the robustness of the rate-distortion performance of the channel-optimized vector quantizer, and reduces the computational time for finding the best rate-punctured convolutional code. Numerical results show that the algorithm attains near optimal performance while having low computational complexity.

Keywords

Vector Quantization Genetic Algorithm Error Correct Coding 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chien-Min Ou
    • 1
  • Wen-Jyi Hwang
    • 2
  • Hung-Chuan Yung
    • 1
  1. 1.Department of Electronics EngineeringChing Yun UniversityChungliTaiwan, ROC
  2. 2.Graduate Institute of Computer Science and Information EngineeringNational Taiwan Normal UniversityTaipeiTaiwan, ROC

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