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Relative Information

Theories and Applications

  • Book
  • © 1990

Overview

Authors:
  1. Guy Jumarie

    1. Department of Mathematics and Computer Science, University of Québec at Montréal, Montréal, Canada

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Part of the book series: Springer Series in Synergetics (SSSYN, volume 47)

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XXII
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  2. Relative Information — What For?

    • Guy Jumarie
    Pages 1-11

  3. Information Theory — The State of the Art

    • Guy Jumarie
    Pages 12-43

  4. A Critical Review of Shannon Information Theory

    • Guy Jumarie
    Pages 44-65

  5. A Theory of Relative Information

    • Guy Jumarie
    Pages 66-99

  6. A Theory of Subjective Information

    • Guy Jumarie
    Pages 100-127

  7. A Unified Approach to Discrete and Continuous Entropy

    • Guy Jumarie
    Pages 128-149

  8. A Unified Approach to Informational Entropies via Minkowskian Observation

    • Guy Jumarie
    Pages 150-179

  9. Entropy of Form and Pattern

    • Guy Jumarie
    Pages 180-220

  10. A Theory of Relative Statistical Decision

    • Guy Jumarie
    Pages 221-248

  11. Concluding Remarks and Outlook

    • Guy Jumarie
    Pages 249-250

  12. Back Matter

    Pages 251-259
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Keywords

About this book

For four decades, information theory has been viewed almost exclusively as a theory based upon the Shannon measure of uncertainty and information, usually referred to as Shannon entropy. Since the publication of Shannon's seminal paper in 1948, the theory has grown extremely rapidly and has been applied with varied success in almost all areas of human endeavor. At this time, the Shannon information theory is a well established and developed body of knowledge. Among its most significant recent contributions have been the use of the complementary principles of minimum and maximum entropy in dealing with a variety of fundamental systems problems such as predic­ tive systems modelling, pattern recognition, image reconstruction, and the like. Since its inception in 1948, the Shannon theory has been viewed as a restricted information theory. It has often been argued that the theory is capable of dealing only with syntactic aspects of information, but not with its semantic and pragmatic aspects. This restriction was considered a v~rtue by some experts and a vice by others. More recently, however, various arguments have been made that the theory can be appropriately modified to account for semantic aspects of in­ formation as well. Some of the most convincing arguments in this regard are in­ cluded in Fred Dretske's Know/edge & Flow of Information (The M.LT. Press, Cambridge, Mass., 1981) and in this book by Guy lumarie.

Authors and Affiliations

  • Department of Mathematics and Computer Science, University of Québec at Montréal, Montréal, Canada

    Guy Jumarie

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