A Criterion for Robust Stability with Respect to Parametric Uncertainties Modeled by Multiplicative White Noise with Unknown Intensity, with Applications to Stability of Neural Networks - Archive ouverte HAL Access content directly
Conference Papers Year : 2016

A Criterion for Robust Stability with Respect to Parametric Uncertainties Modeled by Multiplicative White Noise with Unknown Intensity, with Applications to Stability of Neural Networks

(1) , (2) , (1)
1
2

Abstract

In the present paper a robust stabilization problem of continuous-time linear dynamic systems with Markov jumps and corrupted with multiplicative (state-dependent) white noise perturbations is considered. The robustness analysis is performed with respect to the intensity of the white noises. It is proved that the robustness radius depends on the solution of an algebraic system of coupled Lyapunov matrix equations.
Fichier principal
Vignette du fichier
447583_1_En_23_Chapter.pdf (246.41 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01626925 , version 1 (31-10-2017)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Vasile Dragan, Adrian-Mihail Stoica, Toader Morozan. A Criterion for Robust Stability with Respect to Parametric Uncertainties Modeled by Multiplicative White Noise with Unknown Intensity, with Applications to Stability of Neural Networks. 27th IFIP Conference on System Modeling and Optimization (CSMO), Jun 2015, Sophia Antipolis, France. pp.250-260, ⟨10.1007/978-3-319-55795-3_23⟩. ⟨hal-01626925⟩
42 View
62 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More