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Synergetics pp 69-103 | Cite as

Chance

How Far a Drunken Man Can Walk
  • Hermann Haken
Part of the Springer Series in Synergetics book series (SSSYN, volume 1)

Abstract

While in Chapter 2 we dealt with a fixed probability measure, we now study stochastic processes in which the probability measure changes with time. We first treat models of Brownian movement as example for a completely stochastic motion. We then show how further and further constraints, for example in the frame of a master equation, render the stochastic process a more and more deterministic process.

This Chapter 4, and Chapter 5, are of equal importance for what follows. Since Chapter 4 is somewhat more difficult to read, students may also first read 5 and then 4. On the other hand, Chapter 4 continues directly the line of thought of Chapters 2 and 3. In both cases, chapters with an asterisk in the heading may be omitted during a first reading.

Keywords

Brownian Movement Conditional Probability Markov Process Transition Rate Joint Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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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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