Personal tools
You are here: Home Publications Journal Papers Convergence Rates for Decentralized Consistent Location Parameter Estimation in the Presence of Gaussian Outliers

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

Filed under:
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.

Article [pdf]

Document Actions
« August 2017 »
August
MoTuWeThFrSaSu
123456
78910111213
14151617181920
21222324252627
28293031