Exponential periodicity and stability of delayed neural networks
In this paper, exponential periodicity and stability of delayed neural networks is investigated. Without assuming the boundedness and differentiability of the activation functions, some new sufficient conditions ensuring existence and uniqueness of periodic solution for a general class of neural systems are obtained. The delayed Hopfield network, bidirectional associative memory network, and cellular neural network are special cases of the neural system model considered. (C) 2004 IMACS. Published by Elsevier B.V. All rights reserved.
exponential periodicity delayed neural networks activation functions exponential stability young inequality