Stability analysis for fractional‐order neural networks with time‐varying delay

This paper focuses on the stability analysis for fractional-order neural networks with time-varying delay. A novel Lyapunov's asymptotic stability determination theorem is proved, which can be used for fractional-order systems directly. Different from the classical Lyapunov stability theorem, constraint condition on the derivative of Lyapunov function is revised as an uniformly continuous class-K function in the fractional-order case. Based on this novel Lyapunov stability theorem and free weight matrix method, a new sufficient condition on Lyapunov asymptotic stability of fractional-order Hopfield neural networks is derived by constructing a suitable Lyapunov function. Moreover, two numerical examples are provided to illustrate the effectiveness of these criteria.