时变耦合变时滞非自治神经网络模型的全局同步性分析

Global Synchronization of Non-autonomous Neural Networks with Variable Delays and Variable Couplings

利用Lyapunov泛函方法,对一类时变线性耦合神经网络模型的全局同步性进行了研究.在去掉耦合矩阵的对称性、不可约性和扩散耦合限制的基础上,得到了确保耦合时滞神经网络模型全局同步的充分性条件.所得结果仅依赖于系统中的参数,条件易于验证且不必求矩阵的特征值.

The global synchronization of an array of linearly coupled identical connected time-varying neural networks with time-varying couplings was investigated. Dropping off the symmetry, irreducibility and diffusive coupling connection of the coupling matrix, the sufficient conditions ensuring global synchronization of coupled delayed neural networks were obtained, which are easy to check since these conditions only depend on the parameters in the systems and it is not necessary to solve the eigenvalue of the matrix. The theoretical analysis were verified by numerical simulations.