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    Sampled-data synchronization control for chaotic neural networks subject to actuator saturation

    Access Status
    Fulltext not available
    Authors
    Zeng, Hong-Bing
    Teo, Kok Lay
    He, Y.
    Xu, Honglei
    Wang, Wei
    Date
    2017
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Zeng, H. and Teo, K.L. and He, Y. and Xu, H. and Wang, W. 2017. Sampled-data synchronization control for chaotic neural networks subject to actuator saturation. Neurocomputing. 260: pp. 25-31.
    Source Title
    Neurocomputing
    DOI
    10.1016/j.neucom.2017.02.063
    ISSN
    0925-2312
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/52243
    Collection
    • Curtin Research Publications
    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.

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