Journal of Optimization Theory and Applications

, Volume 149, Issue 1, pp 197-215

First online:

Global Robust Passivity Analysis for Stochastic Interval Neural Networks with Interval Time-Varying Delays and Markovian Jumping Parameters

  • P. BalasubramaniamAffiliated withDepartment of Mathematics, Gandhigram Rural Institute-Deemed University Email author 
  • , G. NagamaniAffiliated withDepartment of Mathematics, Gandhigram Rural Institute-Deemed University

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In this paper, the problem of passivity analysis is investigated for stochastic interval neural networks with interval time-varying delays and Markovian jumping parameters. By constructing a proper Lyapunov-Krasovskii functional, utilizing the free-weighting matrix method and some stochastic analysis techniques, we deduce new delay-dependent sufficient conditions, that ensure the passivity of the proposed model. These sufficient conditions are computationally efficient and they can be solved numerically by linear matrix inequality (LMI) Toolbox in Matlab. Finally, numerical examples are given to verify the effectiveness and the applicability of the proposed results.


Interval time-varying delays Linear matrix inequality (LMI) Lyapunov method Passivity Stochastic interval neural networks