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

0Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.

This article is free to access.

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.

Cite

CITATION STYLE

APA

Dragan, V., Stoica, A. M., & Morozan, T. (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. In IFIP Advances in Information and Communication Technology (Vol. 494, pp. 250–260). Springer New York LLC. https://doi.org/10.1007/978-3-319-55795-3_23

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free