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Neural Processing Letters
Erschienen in: Neural Processing Letters 3/2017

11.10.2016

Existence and Global Exponential Stability of Periodic Solution for a Class of Neutral-Type Neural Networks with Time Delays

verfasst von: Yurong Liu, Bo Du, Ahmed Alsaedi

Erschienen in: Neural Processing Letters | Ausgabe 3/2017

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Abstract

This paper is concerned with the problems of existence and stability of the periodic solution for a class of neutral-type neural networks. The neural network addressed is general where the time delays and difference operator are taken into account. By employing the Mawhin’s continuation theorem, the sufficient condition is obtained to guarantee the existence and uniqueness of the periodic solution for the neutral-type neural networks. By constructing a novel Lyapunov functional, a unified framework is established to derive sufficient conditions for the concerned system to be globally exponentially stable. A numerical example is provided to demonstrate the usefulness of the main results obtained.
Vorheriger Artikel Locality Preserving Collaborative Representation for Face Recognition
Nächster Artikel A Neural Network Approach for Solving Optimal Control Problems with Inequality Constraints and Some Applications

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Metadaten
Titel
Existence and Global Exponential Stability of Periodic Solution for a Class of Neutral-Type Neural Networks with Time Delays
verfasst von
Yurong Liu
Bo Du
Ahmed Alsaedi
Publikationsdatum
11.10.2016
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 3/2017
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-016-9549-3

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