DocumentCode :
930965
Title :
An improved decision-directed detector (Corresp.)
Author :
Kazakos, Dimitri ; Davisson, Lee D.
Volume :
26
Issue :
1
fYear :
1980
fDate :
1/1/1980 12:00:00 AM
Firstpage :
113
Lastpage :
116
Abstract :
A decision-directed detection scheme for multiple hypotheses is developed and analyzed. It is assumed that the probability density functions 
under each of the 
hypotheses are known, and the prior probablities 
are unknown and sequentially estimated on the basis of previous decisions. Using a set of nonlinear transformations of the data and applying results from the stochastic approximation theory, improved algorithms are given for achieving asymptotically unbiased estimates and accelerated convergence to the true priors.
under each of the hypotheses are known, and the prior probablities are unknown and sequentially estimated on the basis of previous decisions. Using a set of nonlinear transformations of the data and applying results from the stochastic approximation theory, improved algorithms are given for achieving asymptotically unbiased estimates and accelerated convergence to the true priors.Keywords :
Parameter estimation; Signal detection; Closed-form solution; Convergence; Data communication; Decoding; Density functional theory; Detectors; Gaussian noise; Parameter estimation; Signal analysis; Yield estimation;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1980.1056124
Filename :
1056124
Link To Document :
