You are not logged in.

Synchronization of memristor-based delayed BAM neural networks with fractional-order derivatives

Rajivganthi, Chinnathambi, Rihan, Fathalla A, Lakshmanan, Shanmugam, Rakkiyappan, Rajan and Muthukumar, Palanisamy 2016, Synchronization of memristor-based delayed BAM neural networks with fractional-order derivatives, Complexity, vol. 21, no. S2, pp. 412-426, doi: 10.1002/cplx.21821.

Attached Files
Name Description MIMEType Size Downloads

Title Synchronization of memristor-based delayed BAM neural networks with fractional-order derivatives
Author(s) Rajivganthi, Chinnathambi
Rihan, Fathalla A
Lakshmanan, ShanmugamORCID iD for Lakshmanan, Shanmugam orcid.org/0000-0002-4622-3782
Rakkiyappan, Rajan
Muthukumar, Palanisamy
Journal name Complexity
Volume number 21
Issue number S2
Start page 412
End page 426
Total pages 15
Publisher Wiley-Blackwell
Place of publication London, Eng.
Publication date 2016-11
ISSN 1076-2787
Keyword(s) fractional-order
memristor-based BAM neural networks
synchronization
time-delays
Summary This article deals with the problem of synchronization of fractional-order memristor-based BAM neural networks (FMBNNs) with time-delay. We investigate the sufficient conditions for adaptive synchronization of FMBNNs with fractional-order 0<a<1. The analysis is based on suitable Lyapunov functional, differential inclusions theory, and master-slave synchronization setup. We extend the analysis to provide some useful criteria to ensure the finite-time synchronization of FMBNNs with fractional-order 1<a<2, using Mittag-Leffler functions, Laplace transform, and linear feedback control techniques. Numerical simulations with two numerical examples are given to validate our theoretical results. Presence of time-delay and fractional-order in the model shows interesting dynamics.
Language eng
DOI 10.1002/cplx.21821
Field of Research 0102 Applied Mathematics
0103 Numerical And Computational Mathematics
0802 Computation Theory And Mathematics
Socio Economic Objective 0 Not Applicable
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2016 Wiley Periodicals, Inc.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089102

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 19 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Mon, 03 Apr 2017, 10:32:06 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.