loading page

Global Asymptotic Synchronization of Fractional Order Multi-linked Memristive Neural Networks with Time-varying Delays via Discontinuous Control
  • +2
  • Shaofang Wang,
  • Lixiang Li,
  • Haipeng Peng,
  • Yixian Yang,
  • Mingwen Zheng
Shaofang Wang
Beijing University of Posts and Telecommunications
Author Profile
Lixiang Li
Beijing University of Posts and Telecommunications
Author Profile
Haipeng Peng
Beijing University of Posts and Telecommunications
Author Profile
Yixian Yang
Beijing University of Posts and Telecommunications
Author Profile
Mingwen Zheng
Shandong University of Technology
Author Profile

Abstract

In this paper, we address the global asymptotic synchronization (GAS) problem of the Master-Slave fractional order multi-linked memristive neural networks (FOMMNNs). Firstly, we propose the FOMMNNs which incorporate the fractional calculus into multi-linked memristive neural networks (MMNNs) for the first time. Then, by utilizing the fractional differential inclusions and set-valued mapping theories, the addressed FOMMNNs with discontinuous state switching at the right-hand side and time-varying delays are converted into the continuous FOMMNNs. Under the frameworks of fractional Caputo derivative and fractional Fillipov solution, by the way of building up appropriate Lyapunov functionals and utilizing some synchronous analysis technology, several sufficient criteria ensuring that the Master-Slave FOMMNNs can realize global asymptotic synchronization (GAS) under two different state-feedback controllers are obtained.

Peer review status:ACCEPTED

12 Mar 2021Submitted to Mathematical Methods in the Applied Sciences
13 Mar 2021Submission Checks Completed
13 Mar 2021Assigned to Editor
20 Mar 2021Reviewer(s) Assigned
31 Mar 2021Review(s) Completed, Editorial Evaluation Pending
01 Apr 2021Editorial Decision: Revise Minor
25 Apr 20211st Revision Received
25 Apr 2021Submission Checks Completed
25 Apr 2021Assigned to Editor
28 Apr 2021Reviewer(s) Assigned
30 Apr 2021Review(s) Completed, Editorial Evaluation Pending
02 May 2021Editorial Decision: Accept