New criterion for finite-time synchronization of fractional order memristor-based neural networks with time delay

Feifei Du and Jun-Guo Lu

Applied Mathematics and Computation, 2021, vol. 389, issue C

Abstract: A new fractional order Gronwall inequality with time delay is developed in this paper. Based on this inequality, a new criterion for finite-time synchronization of fractional order memristor-based neural networks (FMNNs) with time delay is derived. In addition, two numerical examples are exhibited to illustrate the effectiveness of the obtained results.

Keywords: Fractional order neural networks; Finite-time synchronization; Time delay; Memristor (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300320305701
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:389:y:2021:i:c:s0096300320305701

DOI: 10.1016/j.amc.2020.125616

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().