DocumentCode
2620537
Title
A neural-network approach to statistical decision making
Author
Yao, Chia-Yu ; Willson, Alan N., Jr.
Author_Institution
Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA
fYear
1990
fDate
1-3 May 1990
Firstpage
727
Abstract
A decision-making network is required in signal detection. A method is proposed to implement a decision-making network using the Hopfield model. The stability of this structure is analyzed in detail. Two design examples are given, and the error probabilities in both examples are derived. The performance of the network is contrasted with that of a matched filter, and the two are found to be highly comparable
Keywords
decision theory; neural nets; signal detection; statistics; Hopfield model; design examples; error probabilities; matched filter; neural-network approach; signal detection; stability; statistical decision making; Computer architecture; Decision making; Error probability; Filters; Lyapunov method; Neural networks; Signal detection; Stability analysis; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location
New Orleans, LA
Type
conf
DOI
10.1109/ISCAS.1990.112182
Filename
112182
Link To Document