DocumentCode
3427635
Title
Nonlinear Sparse-Graph Codes for Lossy Compression of Discrete Nonredundant Sources
Author
Gupta, Ankit ; Verdu, Sergio
Author_Institution
Princeton Univ., Princeton
fYear
2007
fDate
2-6 Sept. 2007
Firstpage
541
Lastpage
546
Abstract
We propose a scheme to implement lossy data compression for discrete equiprobable sources using block codes based on sparse matrices. We prove asymptotic optimality of the codes for a Hamming distortion criterion. We also present a sub-optimal decoding algorithm, which has near optimal performance for moderate blocklengths.
Keywords
Hamming codes; block codes; data compression; decoding; graph theory; nonlinear codes; sparse matrices; Hamming distortion criterion; block codes; discrete equiprobable sources; discrete nonredundant sources; lossy data compression; nonlinear sparse-graph codes; sparse matrices; sub-optimal decoding algorithm; Channel coding; Error analysis; Error correction codes; Error probability; Lakes; Maximum likelihood decoding; Rate-distortion; Sampling methods; Source coding; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Workshop, 2007. ITW '07. IEEE
Conference_Location
Tahoe City, CA
Print_ISBN
1-4244-1564-0
Electronic_ISBN
1-4244-1564-0
Type
conf
DOI
10.1109/ITW.2007.4313132
Filename
4313132
Link To Document