OPTIMIZATION OF BURGS ENTROPY OVER LINEAR CONSTRAINTS

被引：13

作者：

CENSOR, Y

DEPIERRO, AR

IUSEM, AN

机构：

[1] UNIV CAMPINAS,INST MATEMAT ESTATIST & CIENCIA COMPUTACAO,BR-13081 CAMPINAS,SP,BRAZIL

[2] INST MATEMATICA PURA & APLICADA,BR-22460 RIO DE JANEIRO,RJ,BRAZIL

来源：

APPLIED NUMERICAL MATHEMATICS | 1991年 / 7卷 / 02期

基金：

美国国家卫生研究院;

关键词：

D O I：

10.1016/0168-9274(91)90059-9

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Two special-purpose iterative algorithms for maximization of Burg's entropy function subject to linear inequalities are presented. Both are "row-action" methods which use in each iteration the information contained in only one constraints. One is an underrelaxed Bregman algorithm which requires, at each iterative step, the solution of a system of equations. In contrast with this, the second algorithm employs a closed-form formula for the iterative step. Complete analyses of the convergence for both algorithms are given.

引用

页码：151 / 165

页数：15

共 34 条

[1] F-ENTROPIES, PROBABILITY OF ERROR, AND FEATURE SELECTION [J].