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Neural Processing Letters
Erschienen in: Neural Processing Letters 1/2017

05.12.2016

Exponential Stability of Semi-Markovian Switching Complex Dynamical Networks with Mixed Time Varying Delays and Impulse Control

verfasst von: M. Syed Ali, J. Yogambigai

Erschienen in: Neural Processing Letters | Ausgabe 1/2017

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Abstract

This study examines the problem of exponential stability of complex dynamical networks with impulse control and semi-Markovian switching parameters. By utilizing a supplementary variable technique and a plant transformation, the semi-Markovian switching complex dynamical networks can be equivalently expressed as its associated Markovian switching complex dynamical networks. By applying the Lyapunov stability theory, Jensen’s inequality, Dynkins formula, Schur complement and linear matrix inequality technique, some new delay-dependent conditions are derived to guarantee the exponential stability of the equilibrium point. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the results obtained.
Vorheriger Artikel th Moment Exponential Stability of Hybrid Delayed Reaction–Diffusion Cohen–Grossberg Neural Networks
Nächster Artikel Robustly Exponential Stability Analysis for Discrete-Time Stochastic Neural Networks with Interval Time-Varying Delays

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Metadaten
Titel
Exponential Stability of Semi-Markovian Switching Complex Dynamical Networks with Mixed Time Varying Delays and Impulse Control
verfasst von
M. Syed Ali
J. Yogambigai
Publikationsdatum
05.12.2016
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 1/2017
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-016-9571-5

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