DocumentCode :
3091358
Title :
Distributed Bayesian parameter estimation
Author :
Hoballah, I.Y. ; Varshney, P.K.
Author_Institution :
Syracuse University, Syracuse, New York
Volume :
26
fYear :
1987
fDate :
9-11 Dec. 1987
Firstpage :
2223
Lastpage :
2228
Abstract :
This paper considers the problem of distributed Bayesian parameter estimation. Three commonly used cost criteria namely mean square error, absolute error and uniform cost are employed. Optimum estimation rules at the individual sensors and optimum combining rule are obtained. Suboptimum solutions when the combining rule is restricted to be a linear one are also derived. A simple example is presented for illustration.
Keywords :
Bayesian methods; Costs; Density functional theory; Estimation theory; Mean square error methods; Parameter estimation; Signal processing; State estimation; Vectors; Yield estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1987. 26th IEEE Conference on
Conference_Location :
Los Angeles, California, USA
Type :
conf
DOI :
10.1109/CDC.1987.272937
Filename :
4049702
Link To Document :
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