具有时变延迟的中性复值神经网络的有限时间被动性。

IF 2.6 4区 工程技术 Q1 Mathematics
Haydar Akca, Chaouki Aouiti, Farid Touati, Changjin Xu
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引用次数: 0

摘要

在这项工作中,我们研究了具有时变延迟的中性复值神经网络的有限时间被动性问题。在 Lyapunov 函数、Wirtinger 型不等式技术和线性矩阵不等式(LMI)方法的基础上,推导出了新的充分条件,以确保相关网络模型的有限时间约束性(FTB)和有限时间被动性(FTP)。最后,通过两个数值模拟实例证明了我们的标准的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Finite-time passivity of neutral-type complex-valued neural networks with time-varying delays.

In this work, we investigated the finite-time passivity problem of neutral-type complex-valued neural networks with time-varying delays. On the basis of the Lyapunov functional, Wirtinger-type inequality technique, and linear matrix inequalities (LMIs) approach, new sufficient conditions were derived to ensure the finite-time boundedness (FTB) and finite-time passivity (FTP) of the concerned network model. At last, two numerical examples with simulations were presented to demonstrate the validity of our criteria.

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来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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