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  • Textbook
  • © 2002

The Mathematical Theory of Information

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 684)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xiv
  2. About Information

    • Jan Kåhre
    Pages 1-21
  3. The Law of Diminishing Information

    • Jan Kåhre
    Pages 22-40
  4. General Properties of Information

    • Jan Kåhre
    Pages 41-79
  5. Specific Information Measures

    • Jan Kåhre
    Pages 80-115
  6. Selected Applications

    • Jan Kåhre
    Pages 116-144
  7. Infodynamics

    • Jan Kåhre
    Pages 145-189
  8. Statistical Information

    • Jan Kåhre
    Pages 190-227
  9. Algorithmic Information

    • Jan Kåhre
    Pages 228-261
  10. Continuous Systems

    • Jan Kåhre
    Pages 262-288
  11. Continuous Information

    • Jan Kåhre
    Pages 289-325
  12. Deterministic Dynamics

    • Jan Kåhre
    Pages 326-363
  13. Control and Communication

    • Jan Kåhre
    Pages 364-396
  14. Information Physics

    • Jan Kåhre
    Pages 397-430
  15. The Information Quantum

    • Jan Kåhre
    Pages 431-477
  16. Back Matter

    Pages 478-502

About this book

The general concept of information is here, for the first time, defined mathematically by adding one single axiom to the probability theory. This Mathematical Theory of Information is explored in fourteen chapters: 1. Information can be measured in different units, in anything from bits to dollars. We will here argue that any measure is acceptable if it does not violate the Law of Diminishing Information. This law is supported by two independent arguments: one derived from the Bar-Hillel ideal receiver, the other is based on Shannon's noisy channel. The entropy in the 'classical information theory' is one of the measures conforming to the Law of Diminishing Information, but it has, however, properties such as being symmetric, which makes it unsuitable for some applications. The measure reliability is found to be a universal information measure. 2. For discrete and finite signals, the Law of Diminishing Information is defined mathematically, using probability theory and matrix algebra. 3. The Law of Diminishing Information is used as an axiom to derive essential properties of information. Byron's law: there is more information in a lie than in gibberish. Preservation: no information is lost in a reversible channel. Etc. The Mathematical Theory of Information supports colligation, i. e. the property to bind facts together making 'two plus two greater than four'. Colligation is a must when the information carries knowledge, or is a base for decisions. In such cases, reliability is always a useful information measure. Entropy does not allow colligation.

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access