Vector quantization and signal compression
Vector quantization and signal compression
An introduction to genetic algorithms
An introduction to genetic algorithms
An annealed self-organizing map for source channel coding
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
On the performance and complexity of channel-optimized vector quantizers
IEEE Transactions on Information Theory
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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.