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|Title:||Noise enhancement in robust estimation of location|
|Citation:||IEEE Transactions on Signal Processing, 2018; 66(8):1953-1966|
|Yan Pan, Fabing Duan, François Chapeau-Blondeau, Derek Abbott|
|Abstract:||In this paper, we investigate the noise benefits to maximum likelihood type estimators (M-estimator) for the robust estimation of a location parameter. Two distinct noise benefits are shown to be accessible under these conditions. With symmetric heavy-tailed noise distributions, the asymptotic efficiency of the estimation can be enhanced by injecting extra noise into the M-estimators. With an asymmetric contaminated noise model having a convex cumulative distribution function, we demonstrate that addition of noise can reduce the maximum bias of the median estimator. These findings extend the analysis of stochastic resonance effects for noise-enhanced signal and information processing.|
|Keywords:||Maximum likelihood estimation; robustness; reactive power; noise level; distribution functions; stochastic resonance|
|Rights:||© 2018, IEEE.|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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