Article ID Journal Published Year Pages File Type
410889 Neurocomputing 2006 9 Pages PDF
Abstract

A novel algorithm for jointly optimizing source and channel codes is presented in this paper. The algorithm uses the channel-optimized vector quantization (COVQ) for the source code, and rate-punctured convolutional coding (RCPC) for the channel code. The genetic algorithm (GA) is used for the concurrent design of both source and channel codes. The GA enhances the robustness of the rate–distortion performance of the COVQ to the selection of initial codewords. In addition, it reduces the computational time for realizing the unequal error protection scheme best matched to the COVQ. Numerical results show that the algorithm attains near optimal performance while having low computational complexity.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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