Optimal Estimator for Distributed Anonymous Observers |
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Authors: | Q. Li W. S. Wong |
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Affiliation: | (1) Hong Kong Applied Science and Technology Research Institute Company Limited, Shatin, Hong Kong;(2) Department of Information Engineering, Chinese University of Hong Kong, Shatin, Hong Kong |
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Abstract: | In this paper, we consider a distributed estimation problem in which multiple observations of a signal process are combined via the maximum function for the decision making. A key result established is that, under suitable technical conditions, the optimal decision function can be implemented by means of thresholds. A natural question is how to determine the optimal threshold value. We propose here an algorithm for threshold adjustment by means of training sequences. The algorithm is a variation of the Kiefer-Wolfowitz algorithm with expanding truncations and randomized differences. A result of the paper is to establish the convergence of the algorithm if the variance of observation noises is small enough. |
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Keywords: | Distributed estimation Stochastic approximation Kiefer-Wolfowitz algorithm |
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