陳關榮、汪小帆、李翔編著的《復雜網絡引論—
—模型結構與動力學（第2版英文版）》是為自然科
學、數學和工程領域的研究生以及本科高年級學生編
寫的—本入
門教科書，在第一版的基礎上補充、修訂而成，可以
作為一個學期教學使用的講義，也
可以作為科研參考書或自學讀物。
全書包括兩大部分內容：第一部分是基礎理論，
包括背景材料和信息並附有適量
的練習題，旨在讓讀者熟悉一些最基本的建模方法和
分析技巧。第二部分是應用選
題，包括復雜網絡在幾個代表性領域中的應用研究，
這些章節彼此相對獨立。最後一
章是近年來比較活躍的幾個前沿研究課題的簡介。各
章均附有詳細的關鍵文獻，以幫
助有興趣的讀者能夠很快地進入這些研究領域。
本書保持了第一版的特色，通俗易懂，側重於主
要思想和基本方法的介紹，具有初
等微積分、線性代數和常微分方程的讀者能夠輕松地
學習書中的主要內容。同時增加
了部分新內容，包括基本數理統計和動力繫統基礎、
網絡社團結構、網絡博弈等。

Part I FUNDAMENTAL THEORY
1 Introduction
1.1 Background and Motivation
1.2 A Brief History of Complex Network Research
1.2.1 The Konigsburg SevenBridge Problem
1.2.2 Random Graph Theory
1.2.3 SmallWorld Experiments
1.2.4 Strengths of Weak Ties
1.2.5 Heterogeneity and the WWW
1.3 New Era of ComplexNetwork Studies
Exercises
References
2 Preliminaries
2.1 Elementary Graph Theory
2.1.1 Background
2.1.2 Basic Concepts
2.1.3 Adjacency, Incidence and Laplacian Matrices
2.1.4 Degree Correlation and Assortativity
2.1.5 Some Basic Results on Graphs
2.1.6 Eulerian and Hamiltonian Graphs
2.1.7 Plane and Planar Graphs
2.1.8 Trees and Bipartite Graphs
2.I.9 Directed Graphs
2.1.10 Weighted Graphs
2.1.11 Some Applications
2.2 Elementary Probability and Statistics
2.2.1 Probability Preliminaries
2.2.2 Statistics Preliminaries
2.2.3 Law of Large Numbers and Central Limit Theorem
2.2.4 Markov Chains
2.3 Elementary Dynamical Systems Theory
2.3.1 Background and Motivation
2.3.2 Some Analytical Tools
2.3.3 Chaos in Nonlinear Systems
2.3.4 KolmogorovSinai Entropy
2.3.5 Some Examples of Chaotic Systems
2.3.6 Stabilities of Nonlinear Systems
Exercises
References
3 Network Topologies: Basic Models and Properties
3.1 Introduction
3.2 Regular Networks
3.3 ER RandomGraph Model
3.4 SmallWorld Network Models
3.4.1 WS SmallWorld Network Model
3.4.2 NW SmalL World Network Model
3.4.3 Statistical Properties of SmallWorld Network Models
3.5 Navigable SmallWorld Network Model
3.6 ScaleFree Network Models
3.6.1 BA ScaleFree Network Model
3.6.2 Robustness versus Fragility
3.6.3 Modified BA Models
3.6.4 A Simple Model with PowerLaw Degree Distribution
3.6.5 LocalWorld and MultiLocalWorld Network Models
Exercises
References
Part II APPLICATIONS SELECTED TOPICS
4 Internet: Topology and Modeling
4.1 Introduction
4.2 Topological Properties of the Internet
4.2.1 PowerLaw NodeDegree Distribution
4.2.2 Hierarchical Structure
4.2.3 RichClub Structure
4.2.4 Disassortative Property
4.2.5 Coreness and Betweenness
4.2.6 Growth of the lnternet
4.2.7 RouterLevel lnternet Topology
4.2.8 Geographic Layout of the lnternet
4.3 RandomGraph Network Topology Generator
4.4 Structural Network Topology Generators
4.4.1 Tiers Topology Generator
4.4.2 TransitStub Topology Generator
4.5 ConnectivityBased Network Topology Generators
4.5.1 lnet
4.5.2 BRITE Model
4.5.3 GLP Model
4.5.4 PFP Model
4.5.5 TaNc, Model
4.6 MultiLocalWorld Model
4.6.1 Theoretical Considerations
4.6.2 Numerical Results with Comparison
4.6.3 Performance Comparison
4.7 HOT Model
4.8 Dynamical Behaviors of the Internet Topological Characteristics
4.9 Traffic Fluctuation on Weighted Networks
4.9.1 Weighted Networks
4,9.2 GRD Model
4.9.3 Data Traffic Fluctuations
References
5 Epidemic Spreading Dynamics
5.1 Introduction
5.2 Epidemic Threshold Theory
5.2.1 Epidemic (SI, SIS, SIR) Models
5.2.2 Epidemic Thresholds on Homogenous Networks
5.2.3 Statistical Data Analysis
5.2.4 Epidemic Thresholds on Heterogeneous Networks
5.2.5 Epidemic Thresholds on BA Networks
5.2.6 Epidemic Thresholds on FiniteSized ScaleFree Networks
5.2.7 Epidemic Thresholds on Correlated Networks
5.2.8 SIR Model qf Epidemic Spreading
5.2.9 Epidemic Spreading on Quenched Networks
5.3 Epidemic Spreading on Spatial Networks
5.3.1 Spatial Networks
5.3.2 Spatial Network Models for Infectious Diseases
5.3.3 Impact of Spatial Clustering on Disease Transmissions
5,3.4 LargeScale Spatial Epidemic Spreading
5.3.5 Impact of Human LocationSpecific Contact Patterns
5.4 Immunization on Complex Networks
5.4.1 Random Immunization
5.4.2 Targeted Immunization
5.4.3 Acquaintance Immunization
5.5 Computer Virus Spreading over the Internet
5.5.1 Random ConstantSpread Model
5.5.2 A CompartmentBased Model
5.5.3 Spreading Models of Email Viruses
5.5.4 Effects of Computer Virus on Network Topologies
References
6 Community Structures
6.1 Introduction
6.1.1 Various Scenarios in Real World Social Networks
6.1.2 Generalization of Assortativity
6.2 Community Structure and Modularity
6.2.1 Community Structure
6.2.2 Modularity
6.2.3 Modularity of Weighted and Directed Networks
6.3 ModularityBased Community Detecting Algorithms
6.3.1 CNM Scheme
6.3.2 BGLL Scheme
6.3.3 MultiSlice Community Detection
6.3.4 Detecting Spatial Community Structures
6.4 Other Community Partitioning Schemes
6.4.1 Limitations of the Modularity Measure
6.4.2 Clique Percolation Scheme
6.4.3 EdgeBased Community Detection Scheme
6.4.4 Evaluation Criteria for Community Detection Algorithms
6.5 Some Recent Progress
References
7 Network Games
7.1 Introduction
7.2 TwoPlayer/TwoStrategy Evolutionary Games on Networks
7.2.1 Introduction to Games on Networks
7.2.2 TwoPlayer~TwoStrategy Games on Regular Lattices
7.2.3 TwoPlayer~TwoStrategy Games on BA ScaleFree Networks
7.2.4 TwoPlayer~TwoStrategy Games on Correlated ScaleFree Networks
7.2.5 TwoPlayer/TwoStrategy Games on Clustered ScaleFree Networks
7.3 MultiPlayer/TwoStrategy Evolutionary Games on Networks
7.3.1 Introduction to Public Goods Game
7.3.2 MultiPlayer~TwoStrategy Evolutionary Games on BA Networks
7.3.3 MultiPlayer~TwoStrategy Evolutionary Games on Correlated Scalefree Networks
7.3.4 MultiPlayer/TwoStrategy Evolutionary Games on Clustered Scalefree Networks
7.4 Adaptive Evolutionary Games on Networks
References
8 Network Synchronization
8.1 Introduction
8.2 Complete Synchronization of ContinuousTime Networks
8.2.1 Complete Synchronization of General ContinuousTime Networks
8.2.2 Complete Synchronization of Linearly Coupled ContinuousTime Networks
8.3 Complete Synchronization of Some Typical Dynamical Networks
8.3.1 Complete Synchronization of Regular Networks
8.3.2 Synchronization of SmallWorld Networks
8.3.3 Synchronization of ScaleFree Networks
8.3.4 Complete Synchronization of LocalWorld Networks
8.4 Phase Synchronization
8.4.1 Phase Synchronization of the Kuramoto Model
8.4.2 Phase Synchronization of SmallWorld Networks
8.4.3 Phase Synchronization of ScaleFree Networks
8.4.4 Phase Synchronization of Nonuniformly Coupled Networks
References
9 Network Control
9.1 Introduction
9.2 Spatiotemporal Chaos Control on Regular CML
9.3 Pinning Control of Complex Networks
9.3.1 Augmented Network Approach
9.3.2 Pinning Control of ScaleFree Networks
9.4 Pinning Control of General Complex Networks
9.4.1 Stability Analysis of General Networks under Pinning Control
9.4.2 Pinning and Virtual Control of General Networks
9.4.3 Pinning and Virtual Control of ScaleFree Networks
9.5 TimeDelay Pinning Control of Complex Networks
9.6 Consensus and Flocking Control
References
10 Brief Introduction to Other Topics
10.1 Human Opinion Dynamics
10.2 Human Mobility and Behavioral Dynamics
10.3 Web PageRank, SiteRank and BrowserRank
10.3.1 Methods Based on Edge Analysis
10.3.2 Methods Using Users' Behavior Data
10.4 Recommendation Systems
10.5 Network Edge Prediction
10.6 Living Organisms and Bionetworks
10.7 Cascading Reactions on Networks
References
Index