Synchronization of memristor‐based delayed BAM neural networks with fractional‐order derivatives |
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| Authors: | Chinnathambi Rajivganthi Fathalla A Rihan Shanmugam Lakshmanan Rajan Rakkiyappan Palanisamy Muthukumar |
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| Institution: | 1. Department of Mathematical Sciences, College of Science, United Arab Emirates University, Al‐Ain, UAE;2. Institute for Intelligent Systems Research and Innovation (IISRI), Geelong Waurn Ponds Campus, Deakin University, Australia;3. Department of Mathematics, Bharathiar University, Coimbatore, Tamilnadu, India;4. Department of Mathematics, Gandhigram Rural Institute, Gandhigram, Tamilnadu, India |
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| 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 |
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| Keywords: | fractional‐order memristor‐based BAM neural networks synchronization time‐delays |
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