A new switching control for finite-time synchronization of memristor-based recurrent neural networks. (February 2017)

• Record Type: Journal Article
• Authors: Gao, Jie; Zhu, Peiyong; Alsaedi, Ahmed; Alsaadi, Fuad E.; Hayat, Tasawar
• Is Part Of: Neural networks. Volume 86(2017)
• Page Start: 1
• Page End: 9
• Publication Date: 2017-02
• Subjects: Finite-time synchronization -- Memristor-based neural networks -- Switching control; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2016.10.008
• Languages: English
• ISSNs: 0893-6080

Abstract

Abstract: In this paper, finite-time synchronization (FTS) of memristor-based recurrent neural networks (MNNs) with time-varying delays is investigated by designing a new switching controller. First, by using the differential inclusions theory and set-valued maps, sufficient conditions to ensure FTS of MNNs are obtained under the two cases of 0 < α < 1 and α = 0, and it is derived that α = 0 is the critical value of 0 < α < 1 . Next, it is discussed deeply on the relation between the parameter α and the synchronization time. Then, a new controller with a switching parameter α is designed which can shorten the synchronization time. Finally, some numerical simulation examples are provided to illustrate the effectiveness of the proposed results.