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Type: Journal article
Title: Exponential synchronization for Markovian stochastic coupled neural networks of neutral-type via adaptive feedback control
Author: Chen, H.
Shi, P.
Lim, C.
Citation: IEEE Transactions on Neural Networks and Learning Systems, 2017; 28(7):1618-1632
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Issue Date: 2017
ISSN: 2162-237X
Statement of
Huabin Chen, Peng Shi and Cheng-Chew Lim
Abstract: In this paper, we investigate the adaptive exponential synchronization in both the mean square and the almost sure senses for an array of N identical Markovian stochastic coupled neural networks of neutral-type with time-varying delay and random coupling strength. The generalized Lyapunov theorem of the exponential stability in the mean square for the neutral stochastic Markov system with the time-varying delay is first established. The time-varying delay in the system is assumed to be a bounded measurable function. Then, sufficient conditions to guarantee the exponential synchronization in the mean square for the underlying system are developed under an adaptive feedback controller, which are given in terms of the M-matrix and the algebraic inequalities. Under the same conditions, the almost sure exponential synchronization is also presented. A numerical example is given to show the effectiveness and potential of the proposed theoretical results.
Keywords: Adaptive feedback control; almost sure exponential synchronization; exponential synchronization; Markovian switching; neutral-type; stochastic coupled neural networks (NNs)
Rights: © 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See for more information.
RMID: 0030046915
DOI: 10.1109/TNNLS.2016.2546962
Grant ID:
Appears in Collections:Electrical and Electronic Engineering publications

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