本書內(nèi)容涉及離散和連續(xù)時間動力系統(tǒng)的70個不同主題,共9章,介紹了研究混沌動力系統(tǒng)的一些方法,闡述了將人類免疫缺陷病毒和城市化動態(tài)作為離散映射不太受歡迎的主題的示例,收集了用嚴格證明二維分段映射中混沌的不同方法的結果,對神經(jīng)網(wǎng)絡模型中的魯棒混沌具有的許多說明性示例和方法進行了討論,給出了某些已經(jīng)嚴格確定的二維離散映射的李雅普諾夫指數(shù)的一些結果,討論了利用深入的相關方法來證明某些形式的離散時間系統(tǒng)和連續(xù)時間系統(tǒng)的有界性,展示了全局漸近穩(wěn)定離散時間映射和連續(xù)時間系統(tǒng)的若干形式的某些定義及相關結果等。
Preface
1. Review of Chaotic Dynamics
1.1 Introduction
1.2 Poincare map technique
1.3 Smale horseshoe
1.4 Symbolic dynamics
1.5 Strange attractors
1.6 Basins of attraction
1.7 Density, robustness and persistence of chaos
1.8 Entropies of chaotic attractors
1.9 Period 3 implies chaos
1.10 The Snap-back repeller and the Li-Chen-Marotto theorem
1.11 Shilnikov criterion for the existence of chaos
2. Human lmmunodeficiency Virus and Urbanization Dynamics
2.1 Introduction
2.2 Definition of Human lmmunodeficiency Virus (HIV)
2.3 Modelling the Human Immunodeficiency Virus (HIV)
2.4 Dynamics of sexual transmission of the Human Immunodeficiency Virus
2.5 The effects of variable infectivity on the HIV dynamics
2.6 The CD4 Lymphocyte dynamics in HIV infection
2.7 The viral dynamics of a highly pathogenic Simian/Human Immunodeficiency Virus
2.8 The effects of morphine on Simian lmmunodeficiency Virus Dynamics
2.9 The dynamics of the HIV therapy system
2.10 Dynamics of urbanization
3. Chaotic Behaviors in Piecewise Linear Mappings
3.1 Introduction
3.2 Chaos in one-dimensional piecewise smooth maps
3.3 Chaos in one-dimensional singular maps
3.4 Chaos in 2-D piecewise smooth maps
4. Robust Chaos in Neural Networks Models
4.1 Introduction
4.2 Chaos in neural networks models
4.3 Robust chaos in discrete time neural networks
4.3.1 Robust chaos in I-D piecewise-smooth neural networks
4.3.2 Fragile chaos (blocks with smooth activation function)
4.3.3 Robust chaos (blocks with non-smooth activation function)
4.3.4 Robust chaos in the electroencephalogram model
4.3.5 Robust chaos in Diluted circulant networks
4.3.6 Robust chaos in non-smooth neural networks
4.4 The importance of robust chaos in mathematics and some open problems
5. Estimating Lyapunov Exponents of 2-D Discrete Mappings
5.1 Introduction
5.2 Lyapunov exponents of the discrete hyperchaotic double scroll map
5.3 Lyapunov exponents for a class of 2-D piecewise linear mappings
5.4 Lyapunov exponents of a family of 2-D discrete mappings with separate variables
5.5 Lyapunov exponents of a discontinuous piecewise linear mapping of the plane governed by a simple switching law
5.6 Lyapunov exponents of a modified map-based BVP model
6. Control, Synchronization and Chaotification of Dynamical Systems
6.1 Introduction
6.2 Compound synchronization of different chaotic systems
6.3 Synchronization of 3-D continuous-time quadratic systems using a universal non-linear control law
6.4 Co-existence of certain types of synchronization and its inverse
6.5 Synchronization of 4-D continuous-time quadratic systems using a universal non-linear control law
6.6 Quasi-synchronization of systems with different dimensions
6.7 Chaotification of 3-D linear continuous-time systems using the signum function feedback
6.8 Chaos control problem of a 3-D cancer model with structured uncertainties
6.9 Controlling homoclinic chaotic attractor
6.10 Robustification of 2-D piecewise smooth mappings
6.11 Chaotifying stable n-D linear maps via the controller of any bounded function
7. Boundedness of Some Forms of Quadratic Systems
7.1 Introduction
7.2 Boundedness of certain forms of 3-D quadratic continuous-time systems
7.3 Bounded jerky dynamics
7.3.1 Boundedness of general forms of jerky dynamics
7.3.2 Examples of bounded jerky chaos
7.3.3 Appendix A
7.4 Bounded hyperjerky dynamics
7.5 Boundedness of the generalized 4-D hyperchaotic model containing Lorenz-Stenflo and Lorenz-Haken systems
7.5.1 Estimating the bounds for the Lorenz-Haken system
7.5.2 Estimating the bounds for the Lorenz-Stenflo system
7.6 Boundedness of2-D H~non-like mapping
7.7 Examples of fully bounded chaotic attractors
8. Some Forms of Globally Asymptotically Stable Attra