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Abstract

In chapter 3 the term information was introduced which describes the very often used word information in an exact way. Strictly speaking, this term represents a measure of the width of a statistical distribution function. In particular, an increase of the width of a distribution function leads to an increase of the value of information (see example (3.2)-(3.5)). Due to the fact that such an increase means that the considered system contains more information (in the ordinary sense of the word), it is obvious that the term information can be used to put the often used word information in concrete terms. As it was discussed, such a distribution function can describe both stochastic and deterministic systems. For example, if a Brownian motion is observed, it makes sense to use a statistical distribution function, in which case such a process represents a stochastic process. By contrast, if a written text is considered, a distribution function can be used to describe the probability to find a special word. Such a system represents a typical deterministic system. Both the Brownian motion and the written text contain information (in the ordinary sense of the word). Instead of a written text the human genetic code can be taken as a basis. Then instead of words special molecular configurations occur which represent hereditary information (in the ordinary sense of this word). In order to put the word information in concrete terms, the expression
$$\boxed{{I_m} = - \int_m {\rho \left( \Omega \right)\ln \left[ {\rho \left( \Omega \right)d\Omega } \right]d\Omega } } $$
(8.1)
was introduced. (8.1) can be used to describe natural and artifical systems.

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Copyright information

© Springer Fachmedien Wiesbaden 1993

Authors and Affiliations

  • Volker Achim Weberruß
    • 1
  1. 1.WinterbachDeutschland

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