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Neural Computing and Applications

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01.11.2016 | Original Article

Finite-time stability analysis for fractional-order Cohen–Grossberg BAM neural networks with time delays

verfasst von: C. Rajivganthi, F. A. Rihan, S. Lakshmanan, P. Muthukumar

Erschienen in: Neural Computing and Applications | Ausgabe 12/2018

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Abstract

In this paper, the problem of finite-time stability for a class of fractional-order Cohen–Grossberg BAM neural networks with time delays is investigated. Using some inequality techniques, differential mean value theorem and contraction mapping principle, sufficient conditions are presented to ensure the finite-time stability of such fractional-order neural models. Finally, a numerical example and simulations are provided to demonstrate the effectiveness of the derived theoretical results.

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Titel: Finite-time stability analysis for fractional-order Cohen–Grossberg BAM neural networks with time delays
verfasst von: C. Rajivganthi
F. A. Rihan
S. Lakshmanan
P. Muthukumar
Publikationsdatum: 01.11.2016
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 12/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-016-2641-9

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