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Uncertainty, Entropy and Maximum Entropy Principle — An Overview Read chapter Read first chapter

2003 | OriginalPaper | Chapter

Application of the Maximum (Information) Entropy Principle to Stochastic Processes far from Thermal Equilibrium

Author : Hermann Haken

Published in: Entropy Measures, Maximum Entropy Principle and Emerging Applications

Publisher: Springer Berlin Heidelberg

Included in: Professional Book Archive

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This paper shows how the maximum (information) entropy principle allows the derivation of the short-time propagator from experimental data provided the process is Markovian. From the propagator, the Fokker-Planck equation can be derived. The Lagrange parameters that are used in the maximum information entropy principle can be derived by minimizing the Kullback information.

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Metadata
Title
Application of the Maximum (Information) Entropy Principle to Stochastic Processes far from Thermal Equilibrium
Author
Hermann Haken
Copyright Year
2003
Publisher
Springer Berlin Heidelberg
Book
Entropy Measures, Maximum Entropy Principle and Emerging Applications

Print ISBN: 978-3-642-05531-7

Electronic ISBN: 978-3-540-36212-8

Copyright Year: 2003

DOI
https://doi.org/10.1007/978-3-540-36212-8_3

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