Event-Triggered Exponential Synchronization for Complex-Valued Memristive Neural Networks With Time-Varying Delays

This article solves the event-triggered exponential synchronization problem for a class of complex-valued memristive neural networks with time-varying delays. The drive-response complex-valued memristive neural networks are translated into two real-valued memristive neural networks through the metho...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2020-10, Vol.31 (10), p.4104-4116
Main Authors: Li, Xiaofan, Zhang, Wenbing, Fang, Jian-An, Li, Huiyuan
Format: Article
Language:English
Subjects:
Asymptotic stability
Biological neural networks
Communication networks
Complex-valued memristive neural networks
Delays
event-triggered mechanism
exponential synchronization
Information exchange
Lower bounds
Memristors
Neural networks
Synchronism
Synchronization
Wireless communications
Wireless networks
Zeno behavior
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Summary:This article solves the event-triggered exponential synchronization problem for a class of complex-valued memristive neural networks with time-varying delays. The drive-response complex-valued memristive neural networks are translated into two real-valued memristive neural networks through the method of separating the complex-valued memristive neural networks into real and imaginary parts. In order to reduce the information exchange frequency between the sensor and the controller, a novel event-triggered mechanism with the event-triggering functions is introduced in wireless communication networks. Some sufficient conditions are established to achieve the event-triggered exponential synchronization for drive-response complex-valued memristive neural networks with time-varying delays. In addition, to guarantee that the Zeno behavior cannot occur, a positive lower bound for the interevent times is explicitly derived. Finally, numerical simulations are provided to illustrate the effectiveness and superiority of the obtained theoretical results.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2019.2952186