Title :
A measure for the length of probabilistic dependence
Author :
Kong, Hongwei ; Shwedyk, Ed
Author_Institution :
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
fDate :
29 Jun-4 Jul 1997
Abstract :
A very useful model to describe a random process with memory is the Markov model. The MLSE receiver based on a finite order Markov model is studied in Kong and Shwedyk (1995). It is found that the order of the Markov model, i.e., the length of probabilistic dependence, is the crucial parameter that determines the receiver complexity. An information-theoretic measure for the length of probabilistic dependence is proposed
Keywords :
Markov processes; computational complexity; information theory; maximum likelihood estimation; probability; random processes; receivers; MLSE receiver; Markov model; finite order Markov model; information-theoretic measure; memory; probabilistic dependence length; random process; receiver complexity; Electronic switching systems; Fading; Gaussian processes; Hidden Markov models; Length measurement; Markov processes; Maximum likelihood estimation; Mutual information; Probability density function; Random processes;
Conference_Titel :
Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
Conference_Location :
Ulm
Print_ISBN :
0-7803-3956-8
DOI :
10.1109/ISIT.1997.613406
