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Information and Self-Organization: A Macroscopic Approach to Complex Systems

✍ Scribed by Professor Dr. Dr. h.c. mult. Hermann Haken (auth.)


Publisher
Springer Berlin Heidelberg
Year
1988
Tongue
English
Leaves
204
Series
Springer Series in Synergetics
Category
Library

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✦ Table of Contents


Front Matter....Pages I-XII
The Challenge of Complex Systems....Pages 1-35
From the Microscopic to the Macroscopic World....Pages 36-52
... and Back Again: The Maximum Information Principle (MIP)....Pages 53-64
An Example from Physics: Thermodynamics....Pages 65-68
Application of the Maximum Information Principle to Self-Organizing Systems....Pages 69-73
The Maximum Information Principle for Nonequilibrium Phase Transitions: Determination of Order Parameters, Enslaved Modes, and Emerging Patterns....Pages 74-80
Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points....Pages 81-114
Direct Determination of Lagrange Multipliers....Pages 115-124
Unbiased Modeling of Stochastic Processes: How to Guess Path Integrals, Fokker-Planck Equations and Langevin-Îto Equations....Pages 125-134
Application to Some Physical Systems....Pages 135-139
Transitions Between Behavioral Patterns in Biology. An Example: Hand Movements....Pages 140-152
Pattern Recognition....Pages 153-168
Quantum Systems....Pages 169-181
Concluding Remarks and Outlook....Pages 182-183
Back Matter....Pages 187-196

✦ Subjects


Theoretical, Mathematical and Computational Physics; Laser Technology, Photonics; Quantum Optics; Fluid- and Aerodynamics; Biophysics and Biological Physics


πŸ“œ SIMILAR VOLUMES


Information and Self-Organization: A Mac
✍ Professor Dr. Dr. h.c. mult. Hermann Haken (auth.) πŸ“‚ Library πŸ“… 2006 πŸ› Springer-Verlag Berlin Heidelberg 🌐 English

<p><P>This book presents the concepts needed to deal with self-organizing complex systems from a unifying point of view that uses macroscopic data. The various meanings of the concept "information" are discussed and a general formulation of the maximum information (entropy) principle is used. With t