Uncertainty-based information : elements of generalized information theory

Author(s)

Bibliographic Information

Uncertainty-based information : elements of generalized information theory

George J. Klir, Mark J. Wierman

(Studies in fuzziness and soft computing, v. 15)

Physica-Verlag, c1998

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Note

Includes bibliographical references (p. [147]-164) and index

Description and Table of Contents

Description

The book is an overview of the development of basic ideas and mathematical results regarding measures and principles of uncertainty-based information formalized within the framework of classical set theory, probability theory, fuzzy set theory, possibility theory, and the Dempster-Shafer theory of evidence. The book contains many new results, which had until now not been available in a single monograph. The book is very useful for researchers, but it can also be used as a graduate text.

Table of Contents

  • Introduction: Significance of Uncertainty
  • Uncertainty and Information.- Uncertainty Formalizations: Classical Sets: Terminology and Notation
  • Fuzzy Set Theory
  • Fuzzy Measure Theory
  • Evidence Theory
  • Probability Theory
  • Possibility Theory
  • Overview of Uncertainty Theories.- Uncertainty Measures: Nonspecifity
  • Conflict
  • Aggregate Uncertainty in Evidence Theory
  • Fuzziness
  • Summary of Uncertainty Measures.- Principles of Uncertainty: Principle of Minimum Uncertainty
  • Principle of Maximum Uncertainty
  • Principle of Uncertainty Invariance
  • Summary of Uncertainty Principles.- Conclusions.

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