Impulsive effects on competitive neural networks with mixed delays: Existence and exponential stability analysis

In the proposed research work, the problem of dynamic analysis for a class of existence and global exponential stability of impulsive competitive neural networks (ICNNs) with multiple delays and effects of time scale parameter is investigated. Here the mixed delays include infinite distributed delay and discrete time multiple delays. Firstly, by means of non-linear Lipschitz measure (NLM) and some matrix inequality techniques, the existence and uniqueness of the network equilibrium point is proved, while by fabricating a suitable Lyapunov functional, some new brand of algebraic sufficient conditions is ensured to be globally exponentially stable in voice of linear matrix inequality (LMI). Finally, a numerical example with simulations are shown to illustrate the essence and merits of our obtained analytical results with some existing ones in the available literature. (C) 2018 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.