THE MINMAX INFORMATION MEASURE

被引:23
作者
KAPUR, JN [1 ]
BACIU, G [1 ]
KESAVAN, HK [1 ]
机构
[1] HONG KONG UNIV SCI & TECHNOL, DEPT COMP SCI, KOWLOON, HONG KONG
基金
加拿大自然科学与工程研究理事会;
关键词
D O I
10.1080/00207729508929020
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The importance of finding minimum entropy probability distributions and the value of minimum entropy for a probabilistic system is discussed. A method to calculate these when there are both moment and inequality constraints on probabilities is given and illustrated with examples. It is shown that: information given by moments or inequalities on probabilities can be measured by the reduction in the uncertainty gap (S-max - S-min); and in certain circumstances the inequalities on probabilities can provide significant information about probabilistic systems.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 8 条
  • [1] CHRISTENSEN R, 1981, ENTROPY MINIMAX SOUR, V1
  • [2] INFORMATION THEORY AND STATISTICAL MECHANICS
    JAYNES, ET
    [J]. PHYSICAL REVIEW, 1957, 106 (04): : 620 - 630
  • [3] Kapur J.N., 1992, ENTROPY OPTIMIZATION
  • [4] KAPUR JN, 1993, MEASURES INFORMATION
  • [5] KAPUR JN, 1989, GENERALIZED MAXIMUM
  • [6] A MATHEMATICAL THEORY OF COMMUNICATION
    SHANNON, CE
    [J]. BELL SYSTEM TECHNICAL JOURNAL, 1948, 27 (03): : 379 - 423
  • [7] A MATHEMATICAL THEORY OF COMMUNICATION
    SHANNON, CE
    [J]. BELL SYSTEM TECHNICAL JOURNAL, 1948, 27 (04): : 623 - 656
  • [8] Watanabe S., 1969, KNOWING GUESSING