• DocumentCode
    145642
  • Title

    Sampled-Data Control for State Estimation of Static Neural Networks

  • Author

    Jung, H.Y. ; Park, Jae Hyo ; Lee, S.M.

  • Author_Institution
    Nonlinear Dynamics Group, Yeungnam Univ., Gyeongsan, South Korea
  • Volume
    2
  • fYear
    2014
  • fDate
    10-13 March 2014
  • Firstpage
    301
  • Lastpage
    302
  • Abstract
    In this brief, the problem of sampled-data state estimation for static neural network is investigated. The state-feedback control design method we develop in this paper relies on the information from the sampled states. By constructing a class of Lyapunov function and combining with some inequality, a sufficient condition for the existence of state estimator is derived.
  • Keywords
    Lyapunov methods; control system synthesis; neural nets; state estimation; state feedback; Lyapunov function; sampled-data control; sampled-data state estimation; state estimator; state-feedback control design method; static neural networks; sufficient condition; Biological neural networks; Delays; Neurons; Stability analysis; State estimation; Vectors; Neural networks; Sampled-data; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Computational Intelligence (CSCI), 2014 International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/CSCI.2014.144
  • Filename
    6822355
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=145642