NEW RESULT ON INPUT-OUTPUT FINITE-TIME STABILITY OF FRACTIONAL-ORDER NEURAL NETWORKS

Abstract

In this paper, we investigate the problem of input-output finite-time (IO-FT) stability for a class of fractional-order neural networks with a fractional commensurate order 0 ˂ α ˂ 1. By constructing a simple Lyapunov function and employing a recent result on Caputo fractional derivative of a quadratic function, new sufficient condition is established to guarantee the IO-FT stability of the considered systems. A numerical example is provided to illustrate the effectiveness of the proposed result.