New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed Delays

In this paper, the problem on Lagrange stability of Cohen-Grossberg neural networks (CGNNs) with both mixed delays and general activation functions is considered. By virtue of Lyapunov functional and Halanay delay differential inequality, several new criteria in linear matrix inequalities (LMIs) for...

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Main Authors: Xiaohong Wang, Huan Qi
Format: Article
Language:English
Published: Springer 2013-09-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/25868425.pdf
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author Xiaohong Wang
Huan Qi
author_facet Xiaohong Wang
Huan Qi
author_sort Xiaohong Wang
collection DOAJ
description In this paper, the problem on Lagrange stability of Cohen-Grossberg neural networks (CGNNs) with both mixed delays and general activation functions is considered. By virtue of Lyapunov functional and Halanay delay differential inequality, several new criteria in linear matrix inequalities (LMIs) form for the global exponential stability in Lagrange sense of CGNNs are obtained. Meanwhile, the limitation on the activation functions being bounded, monotonous and differentiable is released, which generalizes and improves those existent results. Moreover, detailed estimations of the globally exponentially attractive sets are given out. It is also verified that outside the globally exponentially attractive set, there is no equilibrium state, periodic state, almost periodic state, and chaos attractor of the CGNNs. Finally, two numerical examples are given to demonstrate the theoretical results.
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spelling doaj.art-5e3af2f01a164ed3b943d7642887637d2022-12-22T02:56:47ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832013-09-016510.1080/18756891.2013.805587New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed DelaysXiaohong WangHuan QiIn this paper, the problem on Lagrange stability of Cohen-Grossberg neural networks (CGNNs) with both mixed delays and general activation functions is considered. By virtue of Lyapunov functional and Halanay delay differential inequality, several new criteria in linear matrix inequalities (LMIs) form for the global exponential stability in Lagrange sense of CGNNs are obtained. Meanwhile, the limitation on the activation functions being bounded, monotonous and differentiable is released, which generalizes and improves those existent results. Moreover, detailed estimations of the globally exponentially attractive sets are given out. It is also verified that outside the globally exponentially attractive set, there is no equilibrium state, periodic state, almost periodic state, and chaos attractor of the CGNNs. Finally, two numerical examples are given to demonstrate the theoretical results.https://www.atlantis-press.com/article/25868425.pdfCohen-Grossberg neural networksLagrange stabilityGlobally exponentially attractive setLinear matrix inequality(LMI)Time-varying delays and finite distributed delays
spellingShingle Xiaohong Wang
Huan Qi
New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed Delays
International Journal of Computational Intelligence Systems
Cohen-Grossberg neural networks
Lagrange stability
Globally exponentially attractive set
Linear matrix inequality(LMI)
Time-varying delays and finite distributed delays
title New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed Delays
title_full New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed Delays
title_fullStr New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed Delays
title_full_unstemmed New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed Delays
title_short New LMI-based Criteria for Lagrange Stability of Cohen-Grossberg Neural Networks with General Activation Functions and Mixed Delays
title_sort new lmi based criteria for lagrange stability of cohen grossberg neural networks with general activation functions and mixed delays
topic Cohen-Grossberg neural networks
Lagrange stability
Globally exponentially attractive set
Linear matrix inequality(LMI)
Time-varying delays and finite distributed delays
url https://www.atlantis-press.com/article/25868425.pdf
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