SIAM Journal on Control and Optimization, Vol.58, No.5, 2854-2870, 2020
FINITE-TIME STABILITY FOR DIFFERENTIAL INCLUSIONS WITH APPLICATIONS TO NEURAL NETWORKS
This 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. New Gronwall-type results are used to estimate the settling time. An example of a neural network which is finite-time stable is given.
Keywords:finite-time stability;differential inclusions;neural networks;viability;Gronwall's inequality;contingent derivative