General stability for a Cohen–Grossberg neural network system

IF 0.9 Q2 MATHEMATICS Arabian Journal of Mathematics Pub Date : 2023-12-15 DOI:10.1007/s40065-023-00452-x
Mohammed D. Kassim, Nasser-Eddine Tatar
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Abstract

Of concern is a Cohen–Grossberg neural network (CGNNs) system taking into account distributed and discrete delays. The class of delay kernels ensuring exponential stability existing in the previous papers is enlarged to an extended class of functions guaranteeing more general types of stability. The exponential and polynomial (or power type) type stabilities becomes particular cases of our result. This is achieved using appropriate Lyapunov-type functionals and the characteristics of the considered class.

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科恩-格罗斯伯格神经网络系统的一般稳定性
科恩-格罗斯伯格神经网络(CGNNs)系统考虑到了分布式和离散延迟,这是一个值得关注的问题。前几篇论文中存在的保证指数稳定性的延迟核类被扩展为保证更一般类型稳定性的扩展函数类。指数型和多项式型(或幂型)稳定性成为我们结果的特殊情况。我们利用适当的 Lyapunov 型函数和所考虑类别的特征来实现这一点。
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来源期刊
CiteScore
2.20
自引率
8.30%
发文量
48
审稿时长
13 weeks
期刊介绍: The Arabian Journal of Mathematics is a quarterly, peer-reviewed open access journal published under the SpringerOpen brand, covering all mainstream branches of pure and applied mathematics. Owned by King Fahd University of Petroleum and Minerals, AJM publishes carefully refereed research papers in all main-stream branches of pure and applied mathematics. Survey papers may be submitted for publication by invitation only.To be published in AJM, a paper should be a significant contribution to the mathematics literature, well-written, and of interest to a wide audience. All manuscripts will undergo a strict refereeing process; acceptance for publication is based on two positive reviews from experts in the field.Submission of a manuscript acknowledges that the manuscript is original and is not, in whole or in part, published or submitted for publication elsewhere. A copyright agreement is required before the publication of the paper.Manuscripts must be written in English. It is the author''s responsibility to make sure her/his manuscript is written in clear, unambiguous and grammatically correct language.
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