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Neural Processing Letters
Erschienen in: Neural Processing Letters 1/2017

24.01.2017

Finite-Time Synchronization of Complex-Valued Neural Networks with Mixed Delays and Uncertain Perturbations

verfasst von: Chao Zhou, Wanli Zhang, Xinsong Yang, Chen Xu, Jianwen Feng

Erschienen in: Neural Processing Letters | Ausgabe 1/2017

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Abstract

This paper concerns the problem of finite-time synchronization for a class of complex-valued neural networks (CVNNs) with both time-varying and infinite-time distributed delays (mixed delays). Both the driving and response CVNNs are disturbed by external uncertain perturbations, which may be nonidentical. A simple state-feedback controller is designed such that the response CVNNs can be synchronized with the driving system in a settling time. By using inequality techniques and constructing some new Lyapunov–Krasovskii functionals, several sufficient conditions are derived to ensure the synchronization. It is discovered that the settling time cannot be estimated when the interested CVNNs exhibit infinite-time distributed delays, while it can be explicitly estimated for the CVNNs with bounded delays. The settling time is dependent on both the delays and the initial value of the error system. Finally, numerical simulations demonstrate the effectiveness of the theoretical results.
Vorheriger Artikel A Generalized Logistic Link Function for Cumulative Link Models in Ordinal Regression
Nächster Artikel Backpropagation for Fully Connected Cascade Networks

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Metadaten
Titel
Finite-Time Synchronization of Complex-Valued Neural Networks with Mixed Delays and Uncertain Perturbations
verfasst von
Chao Zhou
Wanli Zhang
Xinsong Yang
Chen Xu
Jianwen Feng
Publikationsdatum
24.01.2017
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 1/2017
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-017-9590-x

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