Information Theory and Reliable Communication
Information Theory and Reliable Communication
Information Theory: Coding Theorems for Discrete Memoryless Systems
Information Theory: Coding Theorems for Discrete Memoryless Systems
Survey propagation: An algorithm for satisfiability
Random Structures & Algorithms
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)
Source coding, large deviations, and approximate pattern matching
IEEE Transactions on Information Theory
A coding theorem for lossy data compression by LDPC codes
IEEE Transactions on Information Theory
Hash property and coding theorems for sparse matrices and maximum-likelihood coding
IEEE Transactions on Information Theory
Achieving the rate-distortion bound with low-density generator matrix codes
IEEE Transactions on Communications
Achievable complexity-performance tradeoffs in lossy compression
Problems of Information Transmission
Complexity-compression tradeoffs in lossy compression via efficient random codebooks and databases
Problems of Information Transmission
| Hi-index | 754.90 |
We propose a scheme for lossy compression of discrete memorylesssources: The compressor is the decoder of a nonlinear channel code, constructed from a sparse graph. We prove asymptotic optimality of the scheme for any separable (letter-by-letter) bounded distortion criterion. We also present a suboptimal compression algorithm, which exhibits near-optimal performance for moderate block lengths.