Nonlinear Regularization of Inverse Problems for Linear Homogeneous Transforms by Stabilized Hard Thresholding


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Abstract

In this paper we consider the problem of inverting linear homogeneous transforms by Vaguelette–Wavelet decomposition and stabilized hard thresholding of noisy wavelet coefficients. We also prove asymptotic normality and strong consistency of the mean-square risk estimate for this method.

About the authors

O. V. Shestakov

Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University; Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences

Author for correspondence.
Email: oshestakov@cs.msu.su
Russian Federation, Moscow; Moscow

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