Exponential Synchronization of Networked Chaotic Delayed Neural Network by a Hybrid Event Trigger Scheme

• Published in: IEEE transaction on neural networks and learning systems Vol. 29; no. 6; pp. 2558 - 2567
• Main Authors: Fei, Zhongyang, Guan, Chaoxu, Gao, Huijun
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Chaotic communication; Communication networks; Delay effects; Delayed neural network; Delays; exponential synchronization; extended (X; hybrid event trigger scheme; Mathematical models; Network control; Neural networks; Performance indices; Stability criteria; Symmetric matrices; Synchronism; Synchronization; System effectiveness; Z)-dissipativity
• ISSN: 2162-237X; 2162-2388
• DOI: 10.1109/TNNLS.2017.2700321

This paper is concerned with the exponential synchronization for master-slave chaotic delayed neural network with event trigger control scheme. The model is established on a network control framework, where both external disturbance and network-induced delay are taken into consideration. The desired aim is to synchronize the master and slave systems with limited communication capacity and network bandwidth. In order to save the network resource, we adopt a hybrid event trigger approach, which not only reduces the data package sending out, but also gets rid of the Zeno phenomenon. By using an appropriate Lyapunov functional, a sufficient criterion for the stability is proposed for the error system with extended (<inline-formula> <tex-math notation="LaTeX">\mathcal {X} </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\mathcal {Y} </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\mathcal {Z} </tex-math></inline-formula>)-dissipativity performance index. Moreover, hybrid event trigger scheme and controller are codesigned for network-based delayed neural network to guarantee the exponential synchronization between the master and slave systems. The effectiveness and potential of the proposed results are demonstrated through a numerical example.