MMSE decoding for vector quantization over channels with memory

dc.citation.epage	76	en_US
dc.citation.spage	74	en_US
dc.contributor.author	Hsu, HI	en_US
dc.contributor.author	Chang, WW	en_US
dc.contributor.author	Liu, XB	en_US
dc.contributor.author	Koh, SN	en_US
dc.contributor.department	電信工程研究所	zh_TW
dc.contributor.department	Institute of Communications Engineering	en_US
dc.date.accessioned	2014-12-08T15:26:38Z
dc.date.available	2014-12-08T15:26:38Z
dc.date.issued	2002	en_US
dc.description.abstract	This paper presents memory-enhanced extensions of minimum mean-squared error (MMSE) decoding for vector quantization over noisy channels. We also develop a recursive algorithm for computing the transition probabilities of the Gilbert channel, and illustrate its performance in vector quantization of Gauss-Markov sources under noisy channel conditions. Simulation results indicate that the proposed algorithm enables the implementation of an MMSE decoder with increased robustness to channel errors.	en_US
dc.identifier.isbn	0-7803-7549-1	en_US
dc.identifier.journal	2002 IEEE SPEECH CODING WORKSHOP PROCEEDINGS: A PARADIGM SHIFT TOWARD NEW CODING FUNCTIONS FOR THE BROADBAND AGE	en_US
dc.identifier.uri	https://ir.lib.nycu.edu.tw/handle/11536/18929
dc.identifier.wosnumber	WOS:000180140100025
dc.language.iso	en_US	en_US
dc.title	MMSE decoding for vector quantization over channels with memory	en_US
dc.type	Proceedings Paper	en_US

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