Journal of Optimization Theory and Applications

, Volume 149, Issue 1, pp 197–215

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

Authors

    • Department of MathematicsGandhigram Rural Institute-Deemed University
  • G. Nagamani
    • Department of MathematicsGandhigram Rural Institute-Deemed University
Article

DOI: 10.1007/s10957-010-9770-6

Cite this article as:
Balasubramaniam, P. & Nagamani, G. J Optim Theory Appl (2011) 149: 197. doi:10.1007/s10957-010-9770-6

Abstract

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.

Keywords

Interval time-varying delaysLinear matrix inequality (LMI)Lyapunov methodPassivityStochastic interval neural networks

Copyright information

© Springer Science+Business Media, LLC 2011