Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay

Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay

<p/> <p>We derive a new criterion for checking the global stability of periodic oscillation of bidirectional associative memory (BAM) neural networks with periodic coefficients and distributed delay, and find that the criterion relies on the Lipschitz constants of the signal transmission...

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Main Authors: Ma Zhongjun, Wang Yi, Liu Hongli
Format: Article
Language:English
Published: SpringerOpen 2009-01-01
Series:Journal of Inequalities and Applications
Online Access:http://www.journalofinequalitiesandapplications.com/content/2009/385298
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spelling doaj-2b7fb99406054ef7b8a0ceb8244158282020-11-25T00:38:28ZengSpringerOpenJournal of Inequalities and Applications1025-58341029-242X2009-01-0120091385298Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed DelayMa ZhongjunWang YiLiu Hongli<p/> <p>We derive a new criterion for checking the global stability of periodic oscillation of bidirectional associative memory (BAM) neural networks with periodic coefficients and distributed delay, and find that the criterion relies on the Lipschitz constants of the signal transmission functions, weights of the neural network, and delay kernels. The proposed model transforms the original interacting network into matrix analysis problem which is easy to check, thereby significantly reducing the computational complexity and making analysis of periodic oscillation for even large-scale networks.</p>http://www.journalofinequalitiesandapplications.com/content/2009/385298
collection DOAJ
language English
format Article
sources DOAJ
author Ma Zhongjun
Wang Yi
Liu Hongli
spellingShingle Ma Zhongjun
Wang Yi
Liu Hongli
Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay
Journal of Inequalities and Applications
author_facet Ma Zhongjun
Wang Yi
Liu Hongli
author_sort Ma Zhongjun
title Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay
title_short Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay
title_full Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay
title_fullStr Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay
title_full_unstemmed Global Exponential Stability of Periodic Oscillation for Nonautonomous BAM Neural Networks with Distributed Delay
title_sort global exponential stability of periodic oscillation for nonautonomous bam neural networks with distributed delay
publisher SpringerOpen
series Journal of Inequalities and Applications
issn 1025-5834
1029-242X
publishDate 2009-01-01
description <p/> <p>We derive a new criterion for checking the global stability of periodic oscillation of bidirectional associative memory (BAM) neural networks with periodic coefficients and distributed delay, and find that the criterion relies on the Lipschitz constants of the signal transmission functions, weights of the neural network, and delay kernels. The proposed model transforms the original interacting network into matrix analysis problem which is easy to check, thereby significantly reducing the computational complexity and making analysis of periodic oscillation for even large-scale networks.</p>
url http://www.journalofinequalitiesandapplications.com/content/2009/385298
work_keys_str_mv AT mazhongjun globalexponentialstabilityofperiodicoscillationfornonautonomousbamneuralnetworkswithdistributeddelay
AT wangyi globalexponentialstabilityofperiodicoscillationfornonautonomousbamneuralnetworkswithdistributeddelay
AT liuhongli globalexponentialstabilityofperiodicoscillationfornonautonomousbamneuralnetworkswithdistributeddelay
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