Finite-time stability for differential inclusions with applications to neural networks
Optimization and Control
2019-02-22 v2
Abstract
The paper investigates sufficient conditions on a differential inclusion which guarantee that the origin is a finite time stable equilibrium, namely a weak local one, a weak global one or a strong local one. The analysis relies on the existence of a Lyapunov function. A new Gronwall type results are used to estimate the settling time. An example of a neural network which is finite-time stable is given
Cite
@article{arxiv.1804.08440,
title = {Finite-time stability for differential inclusions with applications to neural networks},
author = {Radosław Matusik and Andrzej Nowakowski and Sławomir Plaskacz and Andrzej Rogowski},
journal= {arXiv preprint arXiv:1804.08440},
year = {2019}
}