Improved results on state estimation for neural networks with time-varying delays

摘要

In this paper, some improved results on the state estimation problem for recurrent neural networks with both time-varying and distributed time-varying delays are presented. Through available output measurements, an improved delay-dependent criterion is established to estimate the neuron states such that the dynamics of the estimation error is globally exponentially stable, and the derivative of time-delay being less than 1 is removed, which generalize the existent methods. Finally, two illustrative examples are given to demonstrate the effectiveness of the proposed results.