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Uncertainty-Based Information

Elements of Generalized Information Theory

  • Book
  • © 1999

Overview

Authors:
  1. George J. Klir

    1. Center for Intelligent Systems and Department of Systems Science and Industrial Engineering, Thomas J. Watson School of Engineering and Applied Science, Binghamton University — SUNY, Binghamton, USA

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  2. Mark J. Wierman

    1. Center for Research in Fuzzy Mathematics and Computer Science and Mathematics and Computer Science Department, Creighton University, Omaha, USA

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    You can also search for this author in PubMed   Google Scholar

  • Key developments and results in the area of generalized information theory are introduced
  • This book contains information, which had until now only been available scattered in journals and conference proceedings

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 15)

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Introduction

    • George J. Klir, Mark J. Wierman
    Pages 1-6

  3. Uncertainty Formalizations

    • George J. Klir, Mark J. Wierman
    Pages 7-41

  4. Uncertainty Measures

    • George J. Klir, Mark J. Wierman
    Pages 43-106

  5. Principles of Uncertainty

    • George J. Klir, Mark J. Wierman
    Pages 107-133

  6. Conclusions

    • George J. Klir, Mark J. Wierman
    Pages 135-140

  7. Back Matter

    Pages 141-170
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Keywords

About this book

Information is precious. It reduces our uncertainty in making decisions. Knowledge about the outcome of an uncertain event gives the possessor an advantage. It changes the course of lives, nations, and history itself. Information is the food of Maxwell's demon. His power comes from know­ ing which particles are hot and which particles are cold. His existence was paradoxical to classical physics and only the realization that information too was a source of power led to his taming. Information has recently become a commodity, traded and sold like or­ ange juice or hog bellies. Colleges give degrees in information science and information management. Technology of the computer age has provided access to information in overwhelming quantity. Information has become something worth studying in its own right. The purpose of this volume is to introduce key developments and results in the area of generalized information theory, a theory that deals with uncertainty-based information within mathematical frameworks that are broader than classical set theory and probability theory. The volume is organized as follows.

Authors and Affiliations

  • Center for Intelligent Systems and Department of Systems Science and Industrial Engineering, Thomas J. Watson School of Engineering and Applied Science, Binghamton University — SUNY, Binghamton, USA

    George J. Klir

  • Center for Research in Fuzzy Mathematics and Computer Science and Mathematics and Computer Science Department, Creighton University, Omaha, USA

    Mark J. Wierman

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