Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4947142 | Neurocomputing | 2017 | 9 Pages |
Abstract
In this paper, the sampled-data control is applied to synchronize chaotic neural networks subject to actuator saturation. By employing a time-dependent Lyapunov functional that captures the characteristic information of actual sampling pattern, we derive a local stability condition for the synchronization error systems. By this condition, we design a sampled-data controller to regionally synchronize the drive neural networks and response neural networks subject to actuator saturation. Moreover, an optimization method is given to design the desired sampled-data controller such that the set of admissible initial conditions is maximized. A numerical example is given to demonstrate the effectiveness and merits of the proposed design technique.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hong-Bing Zeng, Kok Lay Teo, Yong He, Honglei Xu, Wei Wang,