Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/127441
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Type: Journal article
Title: Cluster synchronization for neutral stochastic delay networks via intermittent adaptive control
Author: Chen, H.
Shi, P.
Lim, C.
Citation: IEEE Transactions on Neural Networks and Learning Systems, 2019; 30(11):3246-3259
Publisher: Institute of Electrical and Electronics Engineers
Issue Date: 2019
ISSN: 2162-237X
2162-2388
Statement of
Responsibility: 
Huabin Chen, Peng Shi, Cheng-Chew Lim
Abstract: This article studies the problem of cluster synchronization at exponential rates in both the mean square and almost sure senses for neutral stochastic coupled neural networks with time-varying delay via a periodically intermittent pinning adaptive control strategy. The network topology can be symmetric or asymmetric, with each network node being described by neutral stochastic delayed neural networks. When considering the exponential stabilization in the mean square sense for neutral stochastic delay system, the delay inequality approach is used to circumvent the obstacle arising from the coexistence of random disturbance, neutral item, and time-varying delay. The almost surely exponential stabilization is also analyzed with the non- negative semimartingale convergence theorem. Sufficient criteria on cluster synchronization at exponential rates in both the mean square and almost sure senses of the underlying networks under the designed control scheme are derived. The effectiveness of the obtained theoretical results is illustrated by two examples.
Keywords: Cluster synchronization; neutral stochastic coupled neural networks; periodically intermittent pinning adaptive control; stability; time-varying delay
Rights: © 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
DOI: 10.1109/TNNLS.2018.2890269
Grant ID: http://purl.org/au-research/grants/arc/DP170102644
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Computer Science publications

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