Mehrdad Valipour

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In this paper, channel optimized distributed multiple description vector quantization (CDMD) schemes are presented for distributed source coding in symmetric and asymmetric settings. The CDMD encoder is designed using a deterministic annealing approach over noisy channels with packet loss. A minimum mean squared error asymmetric CDMD decoder is proposed for(More)
Quantizer design for lossy compression with mismatched side information (SI) at the decoder is investigated. The statistical dependency between the source and SI is assumed to be a function of a random variable, dependency variable (DV). According to the available information about the DV, three design methods are proposed; namely, minimax solution, Average(More)
Multiple descriptions (MD) with symbol-based turbo (SBT) codes are proposed, where the decoder exploits both non-uniformity of descriptions and their dependencies. A distortion-power adaptive system is obtained by setting an entropy constraint for quantizer design, which together with the MD index assignment (IA), control the level of redundancy at the MD(More)