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Convergence Rates for Decentralized Consistent Location Parameter Estimation in the Presence of Gaussian Outliers

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H. DeliƧ, Signal Processing, Vol. 60, No. 3, pp. 281-288, August 1997.

Abstract- We consider a distributed system where sensors make location parameter estimates using their observations. A central processor collects the local estimates and declares a final estimate based on them. We present a simple study of the convergence properties of three structures where empirical mean and M-estimates are used in various combinations. It is shown that when occasional outliers exist, decentralized estimators that provide robustness at stages where data corruption occurs perform superiorly.

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