Stability And Chaos Synchronization In Delayed Neural Networks

This paper studies the global robust stability for Cohen-Grossberg neural networks (CGNNs) with multiple time-varying delays and global synchronization in an array of coupled delayed neural networks.In Part â… , based on Lyapunov functional method, we study the global robust asymptotic stability for delayed Cohen-Grossberg neural networks, and give a new sufficient condition. Our results do not need the restriction of the symmetry of connection matrices and the bound-ness of the amplification functions, and improve and extend the previous works.In Part â…¡, firstly, we discuss the global synchronization of an array of coupled neural networks with time-varying delay. Based on Lyapunov functional method and matrix inequality techniques, some sufficient criteria are obtained for global exponential synchronization; Secondly, we investigate the global synchronization in an array of coupled delayed neural networks by using Lyapunov functional method and Kronecker product technique, where the inner coupling matrix does't need to be diagonal. The obtained results improve and extend some earlier works, and they are very easy to verify in practice.