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Improved transmission of vector quantized data over noisy channels

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The conventional channel-optimized vector quantization (COVQ) is very powerful in the protection of vector quantization (VQ) data over noisy channels. However, it suffers from the time consuming training process. A soft decoding self-organizing map (SOM) approach for VQ over noisy channels is presented. Compared with the COVQ approach, it does not require a long training time. For AWGN and fading channels, the distortion of the proposed approach is comparable to that of COVQ. Simulation confirmed that our proposed approach is a fast and practical method for VQ over noisy channels. © 2006 Springer-Verlag London Limited.
Original languageEnglish
Pages (from-to)1-9
JournalNeural Computing and Applications
Volume17
Issue number1
DOIs
Publication statusPublished - Jan 2008

Research Keywords

  • Self-organizing map
  • Vector quantization

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