基于非线性测量方法的延迟模糊Cohen-Grossberg神经网络的同步与稳定性分析

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2021-01-11 DOI:10.1080/0952813X.2021.1871663

Meryem Abdelaziz, F. Chérif

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引用次数: 2

摘要

研究一类具有模糊效应和时变时滞的模糊Cohen-Grossberg神经网络(fcgnn)的主从同步问题。给出了建立所考虑模型的指数滞后同步的一些充分条件和新的条件。利用非线性测度方法和Halanay不等式，研究了平衡点的存在性、唯一性和指数稳定性。最后，给出了两个数值模拟实例，验证了所得结果的有效性。

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The synchronization and stability analysis of delayed fuzzy Cohen-Grossberg neural networks via nonlinear measure method

ABSTRACT This paper examines the problem of master-slave synchronization for a class of fuzzy Cohen-Grossberg neural networks (FCGNNs) subject to fuzzy effects and time-delays (time-varying and distributed). Some sufficient and new conditions are given in order to establish the exponential lag synchronization for the considered model. Also, the existence, the uniqueness, and exponential stability of the equilibrium point are investigated, based on the nonlinear measure method and Halanay inequality. Finally, two examples with numerical simulations are given to show the effectiveness of the derived results.

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来源期刊

Journal of Experimental & Theoretical Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

6.10

自引率

4.50%

发文量

审稿时长

>12 weeks

期刊介绍： Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving