On global robust exponential stability of interval neural networks with delays
Changyin Sun, Shiji Song, Chun‐Bo Feng · 2003
In this paper, based on globally Lipschitz continuous activation functions, new conditions ensuring existence, uniqueness and global robust exponential stability of the equilibrium point of interval neural networks with delays are obtained. The delayed Hopfield network, bidirectional associative memory network and cellular neural network are special cases of the network model considered. All the results obtained are generalizations of some recent results reported in the literature for neural networks with constant delays.