Passivity Analysis of Markovian Jumping Neural Networks with Leakage Time-Varying Delays. (18th July 2013)

• Record Type: Journal Article
• Authors: Mala, N.; Sudamani Ramaswamy, A. R.
• Other Names: Benim Ali Cemal Academic Editor.
• Is Part Of: Journal of computational methods in physics. Volume 2013(2013)
• Publication Date: 2013-07-18
• Subjects: Physics -- Data processing -- Periodicals; Mathematical physics -- Data processing -- Periodicals; Mathematical physics -- Data processing; Physics -- Data processing; Electronic journals; Periodicals; Electronic journals; 530.0285
• DOI: 10.1155/2013/172906
• Languages: English
• ISSNs: 2356-7287

Abstract

Abstract : This paper is concerned with the passivity analysis of Markovian jumping neural networks with leakage time-varying delays. Based on a Lyapunov functional that accounts for the mixed time delays, a leakage delay-dependent passivity conditions are derived in terms of linear matrix inequalities (LMIs). The mixed delays includes leakage time-varying delays, discrete time-varying delays, and distributed time-varying delays. By employing a novel Lyapunov-Krasovskii functional having triple-integral terms, new passivity leakage delay-dependent criteria are established to guarantee the passivity performance. This performance not only depends on the upper bound of the time-varying leakage delayσ ( t ) but also depends on the upper bound of the derivative of the time-varying leakage delayσ μ . While estimating the upper bound of derivative of the Lyapunov-Krasovskii functional, the discrete and distributed delays should be treated so as to appropriately develop less conservative results. Two numerical examples are given to show the validity and potential of the developed criteria.