The Global Convergence of the GMED Iterative Algorithm

The Global Convergence of the GMED Iterative Algorithm

Year:    1991

Author:    Jin Tang, Cheng-Shu Wang

Journal of Computational Mathematics, Vol. 9 (1991), Iss. 2 : pp. 125–134

Abstract

In the late 1970's, Wiggins proposed a minimum entropy deconvolution (MED) which has become one of the most important deconvolution methods. He gave a varimax norm $V^4_2$ and a MED iterative procedure. Fortunately, for the last ten years in the practical using, the MED algorithm has never failed to reach a maximizer of the varimax norm. But so far, no theoretical proof has been given to show the convergence of the MED procedure. In this paper, we prove the global convergence of a generalized MED iterative procedure with respect to a generalized varimax norm $V^p_q(q=2,p \gt 2)$.

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/1991-JCM-9385

Journal of Computational Mathematics, Vol. 9 (1991), Iss. 2 : pp. 125–134

Published online:    1991-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    10

Keywords:   

Author Details

Jin Tang

Cheng-Shu Wang