Stability Analysis of Cohen-Grossberg Neural Networks With Multiple Time-Varying Delays

Binbin Gan; Biao Xu; Hao Chen

doi:10.1109/ACCESS.2022.3196772

IEEE Access (Jan 2022)

Stability Analysis of Cohen-Grossberg Neural Networks With Multiple Time-Varying Delays

Binbin Gan,
Biao Xu,
Hao Chen

Affiliations

Binbin Gan: ORCiD; School of Mathematics Science, Huaibei Normal University, Huaibei, China
Biao Xu: ORCiD; School of Mathematics Science, Huaibei Normal University, Huaibei, China
Hao Chen: ORCiD; School of Mathematics Science, Huaibei Normal University, Huaibei, China

DOI: https://doi.org/10.1109/ACCESS.2022.3196772
Journal volume & issue: Vol. 10
pp. 83463 – 83471

Abstract

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By improving a previously introduced Lyapunov functional,this paper addressed the stability issue about neutral-type Cohen-Grossberg neural networks with multiple time-varying delays in the states of neurons and the time derivative of states of neurons, a sufficient condition for global asymptotic stability is obtained. Since the Cohen-Grossberg neural networks considered in this paper is more general than those in the former literature, the obtained result developed stability condition of Cohen-Grossberg neural networks. At the end of the paper, two examples are employed to demonstrate the validity and superiority of the conclusion.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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