Stability And Chaotic Synchronization For Delay Neural Networks And Its Application

Delay neural networks are an important part of neural networks,they exhibit rich dynamical behavior and frequently encountered in signal processing, artificial intelligence, secure communication. For the delay neural networks,stability is the foundation and the most important prerequisite of ensuring neural networks to normal operation. On the other hand, delay chaotic synchronization are widely used in various areas and many research results have been achieved. Therefore, the stability and the chaotic synchronization of delay neural networks have been studied, meanwhile, the chaotic synchronization application to secure communication are introduced. A number of interesting results have been acquired. The main work of this thesis can be briefly described as follows:1. The global robust stability and exponential stability of a class of uncertain neural networks are studies. The existence, uniqueness and stability of the equilibrium point have been prove. By using the Lyapunov method, several sufficient criterion guaranteeing the global robust stability and exponential stability of uncertain neural network with time-varying delays. The examples are given to demonstrate the effectiveness of the obtain results.2. The adaptive synchronization of coupled neural networks with different structures and different parameters are discussed. Based on Lyapunov function and adaptive synchronization control, the adaptive controller and parameter control laws guarantee synchronization of all master and slave systems. Meanwhile, take into account the neural networks with time-varying delay. Some synchronization condition derived even if reality environment on the impact of delays.3. The problem of the chaotic neural networks of different structures and different parameters with discrete and distributed delays is presented. An adaptive lag synchronization strategy is given based on Lyapunov theory, some sufficient conditions of adaptive synchronization controller and parameter control laws guarantee lag synchronization of neural networks. In addition, given the realities of the noise, the synchronization problem with noise perturbed of delay neural networks is studied. Based on Lyapunov theory and adaptive synchronization control method, combined with It o? formula. A well-designed adaptive controller and an adaptive law are given to ensure the synchronization of two delay chaotic neural networks which are of the different structures and different parameters, it has important theoretical and practical significance.4. Chaotic synchronization of delay neural networks apply to secure communication are analyzed. The information signal can be concealed and recovered. To achieve good synchronization performance. The simulation examples are given to shows the effectiveness of the proposed schemes and feasibility.