Minimum entropy and information measure

被引：21

作者：

Yuan, L ^{[1
]}

Kesavan, HK

机构：

[1] Univ Waterloo, Dept Stat, Waterloo, ON N2L 3G1, Canada

[2] Univ Waterloo, Dept Syst Design Engn, Waterloo, ON N2L 3G1, Canada

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS | 1998年 / 28卷 / 03期

关键词：

MinMax measure; minimum entropy; moment constraints; probabilistic system;

D O I：

10.1109/5326.704595

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A previous work of Kapur et al. [5] introduced the MinMax information measure, which is based on both maximum and minimum entropy. The major obstacle far using this measure, in practice, is the difficulty in finding the minimum entropy. An analytical expression has already been developed for calculating the minimum entropy when only variance is specified. Here, an analytical formula is obtained for calculating the minimum entropy when only mean is specified, and numerical examples are given for illustration.

引用

页码：488 / 491

页数：4

共 6 条

[1]

[Anonymous], 1989, Maximum-entropy models in science and engineering

[2] INFORMATION THEORY AND STATISTICAL MECHANICS [J].

JAYNES, ET .

PHYSICAL REVIEW, 1957, 106 (04) :620-630

[3] THE MINMAX INFORMATION MEASURE [J].

KAPUR, JN ;

BACIU, G ;

KESAVAN, HK .

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1995, 26 (01) :1-12

[4]

KAPUR JN, 1994, RELATIONSHIP VARIANC

[5] A MATHEMATICAL THEORY OF COMMUNICATION [J].

SHANNON, CE .

BELL SYSTEM TECHNICAL JOURNAL, 1948, 27 (03) :379-423

[6] PATTERN-RECOGNITION AS A QUEST FOR MINIMUM ENTROPY [J].

WATANABE, S .

PATTERN RECOGNITION, 1981, 13 (05) :381-387

← 1 →