Dynamics of periodic delayed neural networks

摘要: This paper formulates and studies a model of periodic delayed neural networks. can well describe many practical architectures networks, which is generalization some additive networks such as Hopfied cellular under time-varying environment, particularly when the network parameters input stimuli are varied periodically with time. Without assuming smoothness, monotonicity boundedness activation functions, two functional issues on neuronal dynamics this i.e. existence global exponential stability its solutions, investigated. Some explicit conclusive results established, natural extension corresponding existing in literature. Furthermore, examples simulations presented to illustrate nature new results.