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Neural Processing Letters
Erschienen in: Neural Processing Letters 2/2018

09.12.2017

Fixed-Time Synchronization of Coupled Discontinuous Neural Networks with Nonidentical Perturbations

verfasst von: Xusen Zhu, Xinsong Yang, Fuad E. Alsaadi, Tasawar Hayat

Erschienen in: Neural Processing Letters | Ausgabe 2/2018

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Abstract

This paper investigates fixed-time synchronization of coupled neural networks with discontinuous activation functions and nonidentical perturbations under the framework of Filippov solution. In order to overcome uncertainties of the Filippov solution and the effects of nonidentical perturbations, 1-norm based techniques are developed. By designing new state feedback controllers, constructing new Lyapunov functional, and utilizing differential inclusion theory, several sufficient conditions are obtained to ensure that the coupled discontinuous neural networks (CDNNs) to be synchronized in a fixed settling time. Results of this paper improve corresponding ones which only finite-time synchronization can be achieved for CDNNs. Finally, numerical simulations are offered to verify the effectiveness of the theoretical analysis.
Vorheriger Artikel Developmental Network: An Internal Emergent Object Feature Learning
Nächster Artikel Adaptive Finite-Time Synchronization of Neutral Type Dynamical Network with Double Derivative Coupling

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Metadaten
Titel
Fixed-Time Synchronization of Coupled Discontinuous Neural Networks with Nonidentical Perturbations
verfasst von
Xusen Zhu
Xinsong Yang
Fuad E. Alsaadi
Tasawar Hayat
Publikationsdatum
09.12.2017
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 2/2018
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-017-9770-8

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