ORCID Profile
0000-0003-0883-8863
Current Organisation
Vellore Institute of Technology University
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Publisher: Elsevier BV
Date: 06-2014
Publisher: Wiley
Date: 07-02-2015
DOI: 10.1002/CPLX.21503
Publisher: Elsevier BV
Date: 09-2014
Publisher: Elsevier BV
Date: 12-2013
Publisher: Informa UK Limited
Date: 17-11-2016
Publisher: Elsevier BV
Date: 05-2014
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.NEUNET.2014.06.001
Abstract: We extend the notion of Synchronization of memristor-based recurrent neural networks with two delay components based on second-order reciprocally convex approach. Some sufficient conditions are obtained to guarantee the synchronization of the memristor-based recurrent neural networks via delay-dependent output feedback controller in terms of linear matrix inequalities (LMIs). The activation functions are assumed to be of further common descriptions, which take a broad view and recover many of those existing methods. A Lyapunov-Krasovskii functional (LKF) with triple-integral terms is addressed in this paper to condense conservatism in the synchronization of systems with additive time-varying delays. Jensen's inequality is applied in partitioning the double integral terms in the derivation of LMIs and then a new kind of linear combination of positive functions weighted by the inverses of squared convex parameters has emerged. Meanwhile, this paper puts forward a well-organized method to manipulate such a combination by extending the lower bound lemma. The obtained conditions not only have less conservatism but also less decision variables than existing results. Finally, numerical results and its simulations are given to show the effectiveness of the proposed memristor-based synchronization control scheme.
Publisher: Elsevier BV
Date: 05-2014
DOI: 10.1016/J.MBS.2014.02.008
Abstract: In this paper, we investigate a problem of exponential state estimation for Markovian jumping genetic regulatory networks with mode-dependent probabilistic time-varying delays. A new type of mode-dependent probabilistic leakage time-varying delay is considered. Given the probability distribution of the time-delays, stochastic variables that satisfying Bernoulli random binary distribution are formulated to produce a new system which includes the information of the probability distribution. Under these circumstances, the state estimator is designed to estimate the true concentration of the mRNA and the protein of the GRNs. Based on Lyapunov-Krasovskii functional that includes new triple integral terms and decomposed integral intervals, delay-distribution-dependent exponential stability criteria are obtained in terms of linear matrix inequalities. Finally, a numerical ex le is provided to show the usefulness and effectiveness of the obtained results.
No related grants have been discovered for Chandrasekar A.