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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 2/2017

19.09.2015 | Original Article

Global asymptotic stability of impulsive fractional-order BAM neural networks with time delay

verfasst von: Fei Wang, Yongqing Yang, Xianyun Xu, Li Li

Erschienen in: Neural Computing and Applications | Ausgabe 2/2017

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Abstract

In this paper, we study the global asymptotic stability of fractional-order BAM neural networks. We take both time delay and impulsive effects into consideration. Based on Lyapunov stability theorem, fractional Barbalat’s lemma and Razumikhin-type stability theorem, some stability conditions that are independent of the form of specific delays can be obtained. At last, two illustrative examples are given to show the independence of the obtained two main results and to show the effectiveness of the obtained results.
Vorheriger Artikel Prediction of local scour around bridge piers using the ANFIS method
Nächster Artikel PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load

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Metadaten
Titel
Global asymptotic stability of impulsive fractional-order BAM neural networks with time delay
verfasst von
Fei Wang
Yongqing Yang
Xianyun Xu
Li Li
Publikationsdatum
19.09.2015
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 2/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-015-2063-0

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