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Neural Computing and Applications

Erschienen in:

01.04.2014 | Original Article

Anti-periodic solutions for HCNNs with time-varying delays in the leakage terms

verfasst von: Yanli Xu

Erschienen in: Neural Computing and Applications | Ausgabe 5/2014

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Abstract

In this paper, a class of high-order cellular neural networks model is considered with the introduction of time-varying delays in the leakage terms. By using differential inequality techniques, some very verifiable and practical delay-dependent criteria on the existence and global exponential stability of anti-periodic solution for the model are derived. Even for the model without leakage delays, the criteria are shown to be less conservative than many recent publications. Moreover, some examples and remarks are given to demonstrate the feasibility of our method.

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Titel: Anti-periodic solutions for HCNNs with time-varying delays in the leakage terms
verfasst von: Yanli Xu
Publikationsdatum: 01.04.2014
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 5/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-1330-6

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