Linear Complexity Lossy Compressor for Binary Redundant Memoryless Sources
Information Theory
2011-08-19 v2 Disordered Systems and Neural Networks
math.IT
Abstract
A lossy compression algorithm for binary redundant memoryless sources is presented. The proposed scheme is based on sparse graph codes. By introducing a nonlinear function, redundant memoryless sequences can be compressed. We propose a linear complexity compressor based on the extended belief propagation, into which an inertia term is heuristically introduced, and show that it has near-optimal performance for moderate block lengths.
Cite
@article{arxiv.1107.1609,
title = {Linear Complexity Lossy Compressor for Binary Redundant Memoryless Sources},
author = {Kazushi Mimura},
journal= {arXiv preprint arXiv:1107.1609},
year = {2011}
}
Comments
4 pages, 1 figure