LMI Conditions for Fractional Exponential Stability and Passivity Analysis of Uncertain Hopfield Conformable Fractional-Order Neural Networks

This article studies the problem of fractional exponential stability and passivity analysis for Hopfield conformable fractional-order neural networks (CFONNs) subject to uncertainties. First, we derive some less conservative conditions to ensure the fractional exponential stability of Hopfield CFONNs by using the Lyapunov functional method combined with the linear matrix inequality (LMI) approach. Then, by introducing a new definition of passivity analysis for Hopfield CFONNs, an LMI condition is proposed to ensure the passivity analysis of the considered system. Numerical examples are carried out to verify the correctness of the obtained results.