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

K. Balasundaram, R. Raja, A. Pratap and S. Chandrasekaran

Mathematics and Computers in Simulation (MATCOM), 2019, vol. 155, issue C, 290-302

Abstract: 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.

Keywords: Competitive neural networks; Time scale; Global exponential stability; Multiple delays; Impulses (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:155:y:2019:i:c:p:290-302

DOI: 10.1016/j.matcom.2018.05.008

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