Stability and Stabilization of Delayed Neural Networks with Hybrid Impulses

In this paper, the stability and stabilization issues for a class of delayed neural networks with time-varying hybrid impulses are investigated. The hybrid effect of two types of impulses including both stabilizing and destabilizing impulses is considered simultaneously in the analysis of systems. T...

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Published in:Complexity (New York, N.Y.) N.Y.), 2020, Vol.2020 (2020), p.1-9
Main Authors: Lou, Jungang, Wang, Nan, Li, Xuechen, Zou, Kefa, Lu, Jianquan
Format: Article
Language:English
Subjects:
Control stability
Controllers
Dynamical systems
Impulses
Inequality
Neural networks
Pinning
Stability analysis
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container_title Complexity (New York, N.Y.)
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description In this paper, the stability and stabilization issues for a class of delayed neural networks with time-varying hybrid impulses are investigated. The hybrid effect of two types of impulses including both stabilizing and destabilizing impulses is considered simultaneously in the analysis of systems. To characterize the occurrence features of impulses, the concepts of average impulse interval and average impulse strength are employed. Based on the analysis of stability, a pinning impulsive controller which can ensure the global exponential stability of the studied neural networks is designed by pinning a small fraction of neurons. Finally, two numerical examples are given to illustrate the effectiveness of the proposed control schemes for delayed neural networks with hybrid impulses.
doi_str_mv 10.1155/2020/8712027
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subjects Control stability
Controllers
Dynamical systems
Impulses
Inequality
Neural networks
Pinning
Stability analysis
title Stability and Stabilization of Delayed Neural Networks with Hybrid Impulses
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