New stability criterion for Takagi-sugeno fuzzy Cohen-Grossberg neural networks with probabilistic time-varying delays
type: Item
instance of: scholarly article
title: New stability criterion for Takagi-sugeno fuzzy Cohen-Grossberg neural networks with probabilistic time-varying delays
zbMATH Open document ID: 1426.34112
DOI: 10.1155/2017/3793157
author: Xiongrui Wang
author: Ruofeng Rao
author: Shouming Zhong
published in: Mathematical Problems in Engineering
publication date: 2018-11-05T00:00:00Z
review text: Summary: A new global asymptotic stability criterion of Takagi-Sugeno fuzzy Cohen-Grossberg neural networks with probabilistic time-varying delays was derived, in which the diffusion item can play its role. Owing to deleting the boundedness conditions on amplification functions, the main result is a novelty to some extent. Besides, there is another novelty in methods, for Lyapunov-Krasovskii functional is the positive definite form of \(p\) powers, which is different from those of existing literature. Moreover, a numerical example illustrates the effectiveness of the proposed methods.
Mathematics Subject Classification ID: 34K50
Mathematics Subject Classification ID: 34K20
Mathematics Subject Classification ID: 34K36
Mathematics Subject Classification ID: 93E15
zbMATH DE Number: 6972029
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/3793157
OpenAlex ID: W2770415578
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description: scientific article; zbMATH DE number 6972029