Robust H Performance of Discrete-time Neural Networks with Uncertainty and Time-varying Delay

  • M. Syed Ali
  • K. Meenakshi
  • R. Vadivel
  • O. M. Kwon
Regular Papers Control Theory and Applications


In this paper, we are concerned with the robust H problem for a class of discrete-time neural networks with uncertainties. Under a weak assumption on the activation functional, some novel summation inequality techniques and using a new Lyapunov-Krasovskii (L-K) functional, a delay-dependent condition guaranteeing the robust asymptotically stability of the concerned neural networks is obtained in terms of a Linear Matrix Inequality(LMI). It is shown that this stability condition is less conservative than some previous ones in the literature. The controller gains can be derived by solving a set of LMIs. Finally, two numerical examples result are given to illustrate the effectiveness of the developed theoretical results.


H control linear matrix inequality stability time-varying delay 


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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • M. Syed Ali
    • 1
  • K. Meenakshi
    • 1
  • R. Vadivel
    • 1
  • O. M. Kwon
    • 2
  1. 1.Department of MathematicsThiruvalluvar UniversityVelloreIndia
  2. 2.School of Electrical EngineeringChungbuk National UniversityCheongjuKorea

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