DocumentCode
3003214
Title
Application of learning algorithms to hypotheses testing problems
Author
Thathacher, M.A.L. ; Varahan, S.
Author_Institution
Yale University, Connecticut, USA
fYear
1973
fDate
5-7 Dec. 1973
Firstpage
194
Lastpage
198
Abstract
Described in this paper is an application of variable structure stochastic automata to the solution of the hypothesis testing problem. Given the upper bounds on the error probabilities of the two kinds a design procedure for devising an algorithm for the stochastic automaton which ensures a proper decision is developed. The method is illustrated by an application to a simple detection problem of a known constant signal in additive gaussian noise.
Keywords
Additive noise; Algorithm design and analysis; Automatic testing; Gaussian noise; Learning automata; Signal synthesis; Stochastic processes; Upper bound;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control including the 12th Symposium on Adaptive Processes, 1973 IEEE Conference on
Conference_Location
San Diego, CA, USA
Type
conf
DOI
10.1109/CDC.1973.269159
Filename
4045072
Link To Document