SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

A Minimax Approach For Mean Square Denoising

Author(s)

Jean-Christophe Pesquet	IGM - UMR CNRS 8049, Univ. MLV
Yonina Eldar	Dept EE, Technion, Israel

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Abstract

Minimax estimation aims at finding optimal estimators in the worst case situation compatible with the available information. In the present work, we consider the minimax mean square denoising of a random vector using a nonlinear estimator. The data set over which the minimax estimator is looked for takes the general form of a convex set where the correlation matrix of the data is constrained to lie. Also, additional convex contraints on the weights defining the estimator can be taken into account in the proposed approach.