Exponential stability of impulsive complex-valued neural networks with time delay

Zengyun Wang and Xinzhi Liu

Mathematics and Computers in Simulation (MATCOM), 2019, vol. 156, issue C, 143-157

Abstract: This paper studies the stability problem of impulsive complex-valued neural networks with time delay. Firstly, impulses are viewed as disturbance. Criteria on uniqueness and global exponential stability of equilibrium point are established using the Lyapunov function method. A modified version of Halanay-type inequality is used to make the results in Song et al. (2016) much better. Secondly, impulses are used as control input. Sufficient conditions are derived to ensure the exponential stability of the equilibrium point by using the Razumikhin technique. This result explains the dynamics of example 2 in Song et al. (2016), which does not give any theoretical result on impulsive control problem. Two numerical examples are presented to demonstrate the effectiveness of the theorems.

Keywords: Impulsive complex-valued neural networks; Exponential stability; Time delay; Lyapunov function; Razumikhin technique (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:156:y:2019:i:c:p:143-157

DOI: 10.1016/j.matcom.2018.07.006

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