Vol. 3 No. 2 (2019): Vol 3, Iss 2, Year 2019
Articles

Improved stability analysis for Markovian Jump Static Neural Networks with Mode-Dependent Time-Varying Delays

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  • Shyamsundarraj N,
  • Sriraman R,
  • Samidurai R
Shyamsundarraj N
Department of Mathematics, Voorhees College, Vellore-632 001, India
Sriraman R
Department of Mathematics, Thiruvalluvar University, Vellore-632 115, India.
Samidurai R
Department of Mathematics, Thiruvalluvar University, Vellore-632 115, India
DOI: https://doi.org/10.26524/cm58
Published December 30, 2019
Keywords
  • MJSNNs; LKF; Mode-dependent time-varying delays; Integral inequality.
How to Cite
N, S., R, S., & R, S. (2019). Improved stability analysis for Markovian Jump Static Neural Networks with Mode-Dependent Time-Varying Delays. Journal of Computational Mathematica, 3(2), 100-113. https://doi.org/10.26524/cm58

Abstract

This paper investigates the problem of delay-dependent stability analysis for Markovian jump static neural networks (MJSNNs) with mode-dependent time-varying delays. The fundamental objective of this paper is to create novel stability criterion for the considered MJSNNs with less conservatism. A suitable Lyapunov-Krasovskii functional (LKF) is constructed with more system information. By employing integral inequality, a novel delay-dependent sufficient condition is obtained to ensure the asymptotically stability of the equilibrium point. The obtained stability condition is derived and entrenched in terms of linear matrix inequality (LMI) which can be clearly checked by MATLAB LMI control toolbox. At long last, two benchmark illustrative case are given to show the effectiveness of the theoretical result.

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