DocumentCode :
2252952
Title :
Empirical context allocation for multiple dictionary data compression
Author :
Franaszek, Peter ; Thomas, Joy
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
fYear :
1995
fDate :
17-22 Sep 1995
Firstpage :
15
Abstract :
A class of multiple dictionary Lempel-Ziv algorithms is described, where a set of context dependent dictionaries are maintained, and a dictionary chosen based on empirical performance data. These algorithms are conceptually simpler than an earlier approach based on dynamic programming and are also asymptotically optimal
Keywords :
data compression; grammars; optimisation; source coding; trees (mathematics); asymptotically optimal algorithms; context dependent dictionaries; empirical context allocation; empirical performance data; multiple dictionary Lempel-Ziv algorithms; multiple dictionary data compression; source coding; Arithmetic; Convergence; Data compression; Decoding; Dictionaries; Dynamic programming; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
Conference_Location :
Whistler, BC
Print_ISBN :
0-7803-2453-6
Type :
conf
DOI :
10.1109/ISIT.1995.531117
Filename :
531117
Link To Document :
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