Global Asymptotical Stability of Cohen-Grossberg Neural Networks with Time-Varying and Distributed Delays
In this paper, we discuss delayed Cohen-Grossberg neural networks with time-varying and distributed delays and investigate their global asymptotical stability of the equilibrium point. The model proposed in this paper is universal. A set of sufficient conditions ensuring global convergence and globally exponential convergence for the Cohen-Grossberg neural networks with time-varying and distributed delays are given. Most of the existing models and global stability results for Cohen-Grossberg neural networks, Hopfield neural networks and cellular neural networks can be obtained from the theorems given in this paper.
KeywordsNeural Network Exponential Stability Cellular Neural Network Exponential Convergence Hopfield Neural Network
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