The minmax information measure

J. N. Kapur, George Baciu, H. K. Kesavan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

24 Citations (Scopus)

Abstract

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 (Smax- Smin); and in certain circumstances the inequalities on probabilities can provide significant information about probabilistic systems.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalInternational Journal of Systems Science
Volume26
Issue number1
DOIs
Publication statusPublished - 1 Jan 1995
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications

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