Delay Dependent Robust Stability of A Discrete Time Recurrent Neural Network with Time Varying Delays

Authors

  • Elizabeth S. Department of Mathematics, Auxilium College, Gandhi Nagar, Vellore, Tamil Nadu 632006
  • Priya P. Department of Mathematics, Auxilium College, Gandhi Nagar, Vellore, Tamil Nadu 632006

DOI:

https://doi.org/10.26713/jims.v9i3.953

Keywords:

Delay dependent, Recurrent neural network, Lyapunov–Krasovskii, Linear matrix inequality, Robust stability

Abstract

In this paper, the robust stability analysis of a problem is investigated for a class of discrete recurrent neural networks with distributed time varying delays for delay dependent case. The problem is to determine the robust stability by employing Lyapunov–Krasovskii stability theory. The class of neural network under some consideration is globally asymptotically stable if the quadratic matrix inequality involving several parameters is less than zero. Furthermore, a Linear Matrix Inequality (LMI) approach is provided to show the stability analysis. The numerical examples are given to show the usefulness of the proposed robust stability conditions. The numerical simulation is proved using MATLAB.

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References

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Published

2017-10-30
CITATION

How to Cite

S., E., & P., P. (2017). Delay Dependent Robust Stability of A Discrete Time Recurrent Neural Network with Time Varying Delays. Journal of Informatics and Mathematical Sciences, 9(3), 863–872. https://doi.org/10.26713/jims.v9i3.953

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Section

Research Articles