Analysis for the Slow Convergence in Arimoto Algorithm release_msz6ldoj55axdpzpd7zxc2ssra

by Kenji Nakagawa, Yoshinori Takei, Kohei Watabe

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2018  

Abstract

In this paper, we investigate the convergence speed of the Arimoto algorithm. By analyzing the Taylor expansion of the defining function of the Arimoto algorithm, we will clarify the conditions for the exponential or 1/N order convergence and calculate the convergence speed. We show that the convergence speed of the 1/N order is evaluated by the derivatives of the Kullback-Leibler divergence with respect to the input probabilities. The analysis for the convergence of the 1/N order is new in this paper. Based on the analysis, we will compare the convergence speed of the Arimoto algorithm with the theoretical values obtained in our theorems for several channel matrices.
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Type  article
Stage   submitted
Date   2018-09-04
Version   v1
Language   en ?
arXiv  1809.00752v1
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