Globally exponential stability analysis and estimation of the exponential convergence rate for neural networks with multiple time varying delays

Some sufficient conditions for the globally exponential stability of the equilibrium point of neural networks with multiple time varying delays are developed, and the estimation of the exponential convergence rate is presented. The obtained criteria are dependent on time delay, and consist of all the information on the neural networks. The effects of time delay and number of connection matrices of the neural networks on the exponential convergence rate are analyzed, which can give a clear insight into the relation between the exponential convergence rate and the parameters of the neural networks. Two numerical examples are used to demonstrate the effectiveness of the obtained the results.