Stability Analysis of Fractional-order Neural Networks with Delays Based on LMI

In this paper, the uniform stability of Caputo fractional-order neural networks with discrete delay or distributed delay is studied. A suitable quadratic Lyapunov function and a convex Lyapunov function with an appropriate variable upper limit integral term are constructed, respectively. Based on the activation function’s information, the fractional-order Lyapunov direct method and fractional-order differential inequality, two stability criteria for the fractional-order neural networks with delays are derived in the form of linear matrix inequalities. Finally, numerical examples illustrate the validity and feasibility of the theoretical results.