Vector quantization and signal compression
Vector quantization and signal compression
Low Density Codes Achieve theRate-Distortion Bound
DCC '06 Proceedings of the Data Compression Conference
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
A First Course in Information Theory (Information Technology: Transmission, Processing and Storage)
A First Course in Information Theory (Information Technology: Transmission, Processing and Storage)
Good error-correcting codes based on very sparse matrices
IEEE Transactions on Information Theory
Bounds on the maximum-likelihood decoding error probability of low-density parity-check codes
IEEE Transactions on Information Theory
Nested linear/lattice codes for structured multiterminal binning
IEEE Transactions on Information Theory
A coding theorem for lossy data compression by LDPC codes
IEEE Transactions on Information Theory
On the application of LDPC codes to arbitrary discrete-memoryless channels
IEEE Transactions on Information Theory
The ML decoding performance of LDPC ensembles over Zq
IEEE Transactions on Information Theory
Capacity-achieving ensembles for the binary erasure channel with bounded complexity
IEEE Transactions on Information Theory
Variable length lossy coding using an LDPC code
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Hash property and coding theorems for sparse matrices and maximum-likelihood coding
IEEE Transactions on Information Theory
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Research into applying LDPC code theory, which is used for channel coding, to source coding has received a lot of attention in several research fields such as distributed source coding. In this paper, a source coding problem with a fidelity criterion is considered. Matsunaga et al. and Martinian et al. constructed a lossy code under the conditions of a binary alphabet, a uniform distribution, and a Hamming measure of fidelity criterion. We extend their results and construct a lossy code under the extended conditions of a binary alphabet, a distribution that is not necessarily uniform, and a fidelity measure that is bounded and additive and show that the code can achieve the optimal rate, rate-distortion function. By applying a formula for the random walk on lattice to the analysis of LDPC matrices on Zq, where q is a prime number, we show that results similar to those for the binary alphabet condition hold for Zq, the multiple alphabet condition.