Stability Analysis of Impulsive Fuzzy Recurrent Neural Networks with Hybrid Delays

In this paper, the impulsive fuzzy recurrent neural network with both time-varying delays and distributed delays is considered. Applying the idea of vector Lyapunov function, M-matrix theory and analytic methods, several sufficient conditions are obtained to ensure the existence, uniqueness and global exponential stability of equilibrium point for the addressed neural network. Moreover, the estimation of the exponential convergence rate index is provided. These results generalize a few previous known results and remove some restrictions on the neural networks. Two examples are given to show the effectiveness of the obtained results. The method of this paper, which does not make use of Lyapunov functional, is simple and valid for the stability analysis of fuzzy recurrent neural networks with variable delays or/and distributed delays, it is believed that these results are significant and useful for the design and applications of fuzzy neural networks.