Global stability of neural network with distributed delays

Authors:
Hongyong Zhao
Affiliations:
Department of Mathematics, Nanjing University, Nanjing 210093, P. R. China and Department of Mathematics, Xinjiang Normal University, Urumqi 830054, P. R. China
Venue:
Neural, Parallel & Scientific Computations
Year:
2003

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Global stability of neural networks with distributed delays

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Abstract

The paper is devoted to the global asymptotic stability (GAS)of equilibrium point for a class of neural networks with distributed delays. Some sufficient criteria of the the GAS of equilibrium point are derived. We don't assume that the signal propagation functions satisfy the Lipschitz condition and do not require them to be bounded, differentiable or strictly increasing. Moreover, the symmetry of the connection matrix is not also necessary. These conditions are presented in terms of system parameters and have importance leading significance in designs and applications of the GAS for neural networks system with distributed delays. Two examples are also worked out to demonstrate the advantages of our results.