New results on finite-time stability of fractional-order neural networks with time-varying delay

Time: 09:00 to  11:30 Ngày 03/11/2020

Venue/Location: C101, VIASM

Speaker: Nguyễn Trường Thanh

Content:

In this paper, we provide an efficient approach based on fractional calculus and Lyapunov function method to finite-time stability of fractional-order neural networks with time-varying delay. A new proposition on estimating Caputo derivatives of quadratic functions is given. Based on the obtained
result, delay-dependent sufficient conditions for finite-time stability for the system are established in terms of a tractable linear matrix inequality and Mittag-Leffler function. 
A numerical example with simulation is given to demonstrate the effectiveness of the proposed method.