Complex and Adaptive Dynamical Systems

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Complex and Adaptive Dynamical Systems / Claudius Gros

資料種別:: 電子ブック
出版情報:: SpringerLink Books - AutoHoldings
Springer Berlin Heidelberg, 2011
著者名:: Gros, Claudius
ISBN:: 9783642047053 [364204705X]
9783642047060 [3642047068]
書誌ID:: OB00489757

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書誌詳細

言語:

英語

目次情報:

Graph Theory and Small-World Networks / 1：

Graph Theory and Real-World Networks / 1.1：

The Small-World Effect / 1.1.1：

Basic Graph-Theoretical Concepts / 1.1.2：

Properties of Random Graphs / 1.1.3：

Generalized Random Graphs / 1.2：

Graphs with Arbitrary Degree Distributions / 1.2.1：

Probability Generating Function Formalism / 1.2.2：

Distribution of Component Sizes / 1.2.3：

Robustness of Random Networks / 1.3：

Small-World Models / 1.4：

Scale-Free Graphs / 1.5：

Exercises

Further Reading

Chaos, Bifurcations and Diffusion / 2：

Basic Concepts of Dynamical Systems Theory / 2.1：

The Logistic Map and Deterministic Chaos / 2.2：

Dissipation and Adaption / 2.3：

Dissipative Systems and Strange Attractors / 2.3.1：

Adaptive Systems / 2.3.2：

Diffusion and Transport / 2.4：

Random Walks, Diffusion and LÃ©vy Flights / 2.4.1：

The Langevin Equation and Diffusion / 2.4.2：

Noise-Controlled Dynamics / 2.5：

Stochastic Escape / 2.5.1：

Stochastic Resonance / 2.5.2：

Dynamical Systems with Time Delays / 2.6：

Complexity and Information Theory / 3：

Probability Distribution Functions / 3.1：

The Law of Large Numbers / 3.1.1：

Time Series Characterization / 3.1.2：

Entropy and Information / 3.2：

Information Content of a Real-World Time Series / 3.2.1：

Mutual Information / 3.2.2：

Complexity Measures / 3.3：

Complexity and Predictability / 3.3.1：

Algorithmic and Generative Complexity / 3.3.2：

Random Boolean Networks / 4：

Introduction / 4.1：

Random Variables and Networks / 4.2：

Boolean Variables and Graph Topologies / 4.2.1：

Coupling Functions / 4.2.2：

Dynamics / 4.2.3：

The Dynamics of Boolean Networks / 4.3：

The Flow of Information Through the Network / 4.3.1：

The Mean-Field Phase Diagram / 4.3.2：

The Bifurcation Phase Diagram / 4.3.3：

Scale-Free Boolean Networks / 4.3.4：

Cycles and Attractors / 4.4：

Quenched Boolean Dynamics / 4.4.1：

The K = 1 Kauffman Network / 4.4.2：

The K = 2 Kauffman Network / 4.4.3：

The K = N Kauffman Network / 4.4.4：

Applications / 4.5：

Living at the Edge of Chaos / 4.5.1：

The Yeast Cell Cycle / 4.5.2：

Application to Neural Networks / 4.5.3：

Cellular Automata and Self-Organized Criticality / 5：

The Landau Theory of Phase Transitions / 5.1：

Criticality in Dynamical Systems / 5.2：

1/f Noise / 5.2.1：

Cellular Automata / 5.3：

Conway's Game of Life / 5.3.1：

The Forest Fire Model / 5.3.2：

The Sandpile Model and Self-Organized Criticality / 5.4：

Random Branching Theory / 5.5：

Branching Theory of Self-Organized Criticality / 5.5.1：

Galton-Watson Processes / 5.5.2：

Application to Long-Term Evolution / 5.6：

Darwinian Evolution, Hypercycles and Game Theory / 6：

Mutations and Fitness in a Static Environment / 6.1：

Deterministic Evolution / 6.3：

Evolution Equations / 6.3.1：

Beanbag Genetics - Evolutions Without Epistasis / 6.3.2：

Epistatic Interactions and the Error Catastrophe / 6.3.3：

Finite Populations and Stochastic Escape / 6.4：

Strong Selective Pressure and Adaptive Climbing / 6.4.1：

Adaptive Climbing Versus Stochastic Escape / 6.4.2：

Prebiotic Evolution / 6.5：

Quasispecies Theory / 6.5.1：

Hypercycles and Autocatalytic Networks / 6.5.2：

Coevolution and Game Theory / 6.6：

Synchronization Phenomena / 7：

Frequency Locking / 7.1：

Synchronization of Coupled Oscillators / 7.2：

Synchronization with Time Delays / 7.3：

Synchronization via Aggregate Averaging / 7.4：

Synchronization via Causal Signaling / 7.5：

Synchronization and Object Recognition in Neural Networks / 7.6：

Synchronization Phenomena in Epidemics / 7.7：

Elements of Cognitive Systems Theory / 8：

Foundations of Cognitive Systems Theory / 8.1：

Basic Requirements for the Dynamics / 8.2.1：

Cognitive Information Processing Versus Diffusive Control / 8.2.2：

Basic Layout Principles / 8.2.3：

Learning and Memory Representations / 8.2.4：

Motivation, Benchmarks and Diffusive Emotional Control / 8.3：

Cognitive Tasks / 8.3.1：

Internal Benchmarks / 8.3.2：

Competitive Dynamics and Winning Coalitions / 8.4：

General Considerations / 8.4.1：

Associative Thought Processes / 8.4.2：

Autonomous Online Learning / 8.4.3：

Environmental Model Building / 8.5：

The Elman Simple Recurrent Network / 8.5.1：

Universal Prediction Tasks / 8.5.2：

Solutions / 9：

Solutions to the Exercises of Chapter 1

Solutions to the Exercises of Chapter 2

Solutions to the Exercises of Chapter 3

Solutions to the Exercises of Chapter 4

Solutions to the Exercises of Chapter 5

Solutions to the Exercises of Chapter 6

Solutions to the Exercises of Chapter 7

Solutions to the Exercises of Chapter 8

Index

Graph Theory and Small-World Networks / 1：

Graph Theory and Real-World Networks / 1.1：

The Small-World Effect / 1.1.1：

Basic Graph-Theoretical Concepts / 1.1.2：

Properties of Random Graphs / 1.1.3：

Generalized Random Graphs / 1.2：

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