DocumentCode :
941934
Title :
Complexity of strings in the class of Markov sources
Author :
Rissanen, Jorma
Volume :
32
Issue :
4
fYear :
1986
fDate :
7/1/1986 12:00:00 AM
Firstpage :
526
Lastpage :
532
Abstract :
Shannon´s self-information of a string is generalized to its complexity relative to the class of finite-state-machine (FSM) defined sources. Unlike an earlier generalization, the new one is valid for both short and long strings. The definition is justified in part by a theorem stating that, asymptotically, the mean complexity provides a tight lower bound for the mean length of all so-called regular codes. This also generalizes Shannon´s noiseless coding theorem. For a large subclass of FSM sources a simple algorithm is described for computing the complexity.
Keywords :
Markov processes; Source coding; Codes; Entropy; Inference algorithms; Information theory; Length measurement; Mathematical model; Predictive models;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1986.1057210
Filename :
1057210
Link To Document :
بازگشت