Synergetics pp 41-67 | Cite as


How to Be Unbiased
  • Hermann Haken
Part of the Springer Series in Synergetics book series (SSSYN, volume 1)


In this chapter we want to show how, by some sort of new interpretation of probability theory, we get an insight into a seemingly quite different discipline, namely information theory. Consider again the sequence of tossing a coin with outcomes 0 and 1. Now interpret 0 and 1 as a dash and dot of a Morse alphabet. We all know that by means of a Morse alphabet we can transmit messages so that we may ascribe a certain meaning to a certain sequence of symbols. Or, in other words, a certain sequence of symbols carries information. In information theory we try to find a measure for the amount of information.


Partition Function Internal Energy Information Gain Information Entropy Entropy Density 
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Some Basic Ideas

  1. L. Brillouin: Science and Information Theory (Academic Press, New York-London 1962)zbMATHGoogle Scholar
  2. L. Brillouin: Scientific Uncertainty and Information (Academic Press, New York-London 1964)zbMATHGoogle Scholar
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Information Gain: An Illustrative Derivation

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Information Entropy and Constraints

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An Example from Physics: Thermodynamics

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An Approach to Irreversible Thermodynamics

  1. A. Katchalsky, P. F. Curran: Nonequilibrium Thermodynamics in Biophysics (Harvard University Press, Cambridge Mass. 1967)Google Scholar
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Entropy—Curse of Statistical Mechanics?

  1. E. T. Jaynes: Information Theory. In Statistical Physics, Brandeis Lectures, Vol. 3 (W. A. Benjamin, New York 1962)Google Scholar
  2. A. Münster: In Encyclopedia of Physics, ed. by S. Flügge, Vol. III/2: Principles of Thermodynamics and Statistics (Springer, Berlin-Göttingen-Heidelberg 1959)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1983

Authors and Affiliations

  • Hermann Haken
    • 1
  1. 1.Institut für Theoretische PhysikUniversität StuttgartStuttgart 80Fed. Rep. of Germany

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