Chaos theory is an important content in nonlinear sciences and has applications in various fields such as biology， economics， secure communication， and engineering systems. As a branch of nonlinear science， the neural network has complex dynamic behaviors， such as instability， bifurcation and chaos. With the rapid development of modern science and technology， and the wide application of chaos synchronization，chaos synchronization control of neural networks has attracted wide attention in the academic community.The book is divided into six chapters. In Chapter 1， we introduce the background of chaotic neural networks. Chapter 2 investigates the problem of designing sampled-data controller for master-slave synchronization of chaotic Lure systems with time delay. The problem of the sampled-data synchronization control for delayed chaotic neural networks via free-matrix-based time-dependent discontinuous Lyapunov functional approach is discussed in Chapter 3.Chapter 4 proposes a new discontinuous Lyapunov functional approach to research sampled-data synchronization control of chaotic neural networks with mixed delays. In Chapter 5， we mainly discuss the exponential synchronization problem of chaotic neural networks with mixed delays via the sampled-data control. The mean square delay-distribution-dependent exponential synchronization problem of Markovian jumpingdiscrete-time chaotic neural networks with random delays is investigated in Chapter 6.