Synchronization of memristor‐based delayed BAM neural networks with fractional‐order derivatives. (17th August 2016)

• Record Type: Journal Article
• Authors: Rajivganthi, Chinnathambi; Rihan, Fathalla A.; Lakshmanan, Shanmugam; Rakkiyappan, Rajan; Muthukumar, Palanisamy
• Is Part Of: Complexity. Volume 21(2016)Supplement 2
• Page Start: 412
• Page End: 426
• Publication Date: 2016-08-17
• Subjects: fractional‐order -- memristor‐based BAM neural networks -- synchronization -- time‐delays; Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1002/cplx.21821
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : 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 < α < 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 < α < 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. © 2016 Wiley Periodicals, Inc. Complexity 21: 412–426, 2016