Distributed Bayesian parameter estimation

1 December 1987

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 26, 2223-2228
https://doi.org/10.1109/cdc.1987.272937

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
PARAMETER ESTIMATION
COSTS
SIGNAL PROCESSING
STATE ESTIMATION
YIELD ESTIMATION
ESTIMATION THEORY
MEAN SQUARE ERROR METHODS
VECTORS
DENSITY FUNCTIONAL THEORY

This publication has 0 references indexed in Scilit: