Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/117366
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Type: Journal article
Title: Pinning impulsive synchronization for stochastic reaction-diffusion dynamical networks with delay
Author: Chen, H.
Shi, P.
Lim, C.
Citation: Neural Networks, 2018; 106:281-293
Publisher: Elsevier
Issue Date: 2018
ISSN: 0893-6080
1879-2782
Statement of
Responsibility: 
Huabin Chen, Peng Shi, Cheng-Chew Lim
Abstract: This paper considers the problem of the asymptotic synchronization in mean square for stochastic reaction–diffusion complex dynamical networks with infinite delay driven by the Wiener processes in the infinite dimensional space under the pinning impulsive control. Two types of the impulsive controllers are proposed: the first is a single pinning impulsive controller on the first node, and the second is the pinning impulsive controller on a small portion of the network nodes. By using the variation-of-constant formula and the fixed point theorem, the asymptotic behavior of impulsive differential equations with infinite delay is first analyzed. Then, by introducing some operators in the abstract space, the networks are transformed into a set of stochastic coupled impulsive partial differential equations in Hilbert space. Under these two pinning impulsive control types, the asymptotic stability in mean square of stochastic coupled partial differential equations is examined by Lyapunov function approach and the comparison principle. The asymptotic synchronization in mean square of stochastic reaction–diffusion dynamical networks can be realized for these two pinning impulsive control schemes. One example is provided to present the potential application of the theoretic results obtained.
Keywords: Asymptotic synchronization; pinning impulsive control; stochastic coupled neural networks; delay; reaction-diffusion
Rights: © 2018 Elsevier Ltd. All rights reserved.
DOI: 10.1016/j.neunet.2018.07.009
Grant ID: http://purl.org/au-research/grants/arc/DP170102644
Published version: http://dx.doi.org/10.1016/j.neunet.2018.07.009
Appears in Collections:Aurora harvest 8
Electrical and Electronic Engineering publications

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