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

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

Table of Contents

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    Book Overview
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    Chapter 1 The Challenge of Complex Systems
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    Chapter 2 From the Microscopic to the Macroscopic World ...
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    Chapter 3 ... and Back Again: The Maximum Information Principle (MIP)
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    Chapter 4 An Example from Physics: Thermodynamics
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    Chapter 5 Application of the Maximum Information Principle to Self-Organizing Systems
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    Chapter 6 The Maximum Information Principle for Nonequilibrium Phase Transitions: Determination of Order Parameters, Enslaved Modes, and Emerging Patterns
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    Chapter 7 Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points
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    Chapter 8 Direct Determination of Lagrange Multipliers
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    Chapter 9 Unbiased Modeling of Stochastic Processes: How to Guess Path Integrals, Fokker-Planck Equations and Langevin-Îto Equations
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    Chapter 10 Application to Some Physical Systems
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    Chapter 11 Transitions Between Behavioral Patterns in Biology. An Example: Hand Movements
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    Chapter 12 Pattern Recognition. Unbiased Guesses of Processes: Explicit Determination of Lagrange Multipliers
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    Chapter 13 Information Compression in Cognition: The Interplay between Shannon and Semantic Information
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    Chapter 14 Quantum Systems
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    Chapter 15 Quantum Information
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    Chapter 16 Quantum Computation
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    Chapter 17 Concluding Remarks and Outlook
Attention for Chapter 7: Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points
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Chapter title
Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points
Chapter number 7
Book title
Information and Self-Organization
Published by
Springer, Berlin, Heidelberg , January 2006
DOI 10.1007/3-540-33023-2_7
Book ISBNs
978-3-54-033021-9, 978-3-54-033023-3
View on publisher site

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