多权重耦合分数阶反应扩散神经网络的外同步和外 H∞ 同步

IF 6 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Neural Networks Pub Date : 2024-11-09 DOI:10.1016/j.neunet.2024.106893

Jin-Liang Wang, Si-Yang Wang, Yan-Ran Zhu, Tingwen Huang

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引用次数: 0

摘要

本文介绍了多态或空间扩散耦合分数阶反应扩散神经网络，并讨论了这些耦合分数阶反应扩散神经网络（CFRNN）的外同步和外H∞同步问题。利用李亚普诺夫函数法、拉普拉斯变换和不等式技术，得到了 CFRNN 的一些外同步条件。此外，还提供了一些标准来确保 CFRNN 的外同步 H∞。最后，基于两个数值示例验证了推导出的外同步和外 H∞ 同步条件。

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Outer synchronization and outer H_∞ synchronization for coupled fractional-order reaction-diffusion neural networks with multiweights.

This paper introduces multiple state or spatial-diffusion coupled fractional-order reaction-diffusion neural networks, and discusses the outer synchronization and outer H_∞ synchronization problems for these coupled fractional-order reaction-diffusion neural networks (CFRNNs). The Lyapunov functional method, Laplace transform and inequality techniques are utilized to obtain some outer synchronization conditions for CFRNNs. Moreover, some criteria are also provided to make sure the outer H_∞ synchronization of CFRNNs. Finally, the derived outer and outer H_∞ synchronization conditions are validated on the basis of two numerical examples.

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来源期刊

Neural Networks 工程技术-计算机：人工智能

CiteScore

13.90

自引率

7.70%

发文量

425

审稿时长

67 days

期刊介绍： Neural Networks is a platform that aims to foster an international community of scholars and practitioners interested in neural networks, deep learning, and other approaches to artificial intelligence and machine learning. Our journal invites submissions covering various aspects of neural networks research, from computational neuroscience and cognitive modeling to mathematical analyses and engineering applications. By providing a forum for interdisciplinary discussions between biology and technology, we aim to encourage the development of biologically-inspired artificial intelligence.