DocumentCode
1197744
Title
Estimation for discrete Markov random fields observed in Gaussian noise
Author
Elliott, Robert J. ; Aggoun, Lakhdar
Author_Institution
Dept. of Math. Sci., Alberta Univ., Edmonton, Alta., Canada
Volume
40
Issue
5
fYear
1994
fDate
9/1/1994 12:00:00 AM
Firstpage
1600
Lastpage
1603
Abstract
A finite state Markov random field is observed in Gaussian noise. Changes of measures are defined under which all random variables of the signal are independent and uniformly distributed over the finite state space and all random variables of the observation are independent and N(0,1). The problem of estimating the most likely signal given the observations is treated in a related form by introducing probabilities over the possible signals
Keywords
Markov processes; parameter estimation; probability; random processes; signal detection; stochastic processes; Gaussian noise; discrete Markov random fields; finite state space; most likely signal; probabilities; random variables; Additive noise; Decision feedback equalizers; Gaussian noise; Lattices; Markov random fields; Maximum likelihood detection; Maximum likelihood estimation; Random variables; State-space methods; Viterbi algorithm;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.333873
Filename
333873
Link To Document