Title :
Hash property and Wyner-Ziv source coding by using sparse matrices and maximum-likelihood coding
Author :
Muramatsu, Jun ; Miyake, Shigeki
Author_Institution :
NTT Commun. Sci. Labs., NTT Corp., Kyoto
Abstract :
The aim of this paper is to prove the achievability of the Wyner-Ziv source coding problem by using sparse matrices and maximal-likelihood (ML) coding. To this end, the notion of a hash property for an ensemble of functions is introduced. For example, an ensemble of q-ary sparse matrices satisfies the hash property. Based on this property, it is proved that the rate of codes using sparse matrices and maximal-likelihood (ML) coding can achieve the optimal rate.
Keywords :
cryptography; maximum likelihood decoding; source coding; sparse matrices; ML coding; Wyner-Ziv source coding problem; hash property; maximum-likelihood coding; sparse matrices; Approximation methods; Electronic mail; Laboratories; Linear code; Maximum likelihood decoding; Nonlinear distortion; Source coding; Sparse matrices; Sufficient conditions; Technological innovation; hash functions; linear codes; maximum-likelihood eoncoding/decoding; shannon theory; sparse matrix; the Wyner-Ziv problem;
Conference_Titel :
Information Theory, 2008. ISIT 2008. IEEE International Symposium on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-2256-2
Electronic_ISBN :
978-1-4244-2257-9
DOI :
10.1109/ISIT.2008.4595021