Dynamics in fractional-order neural networks

This paper investigates a general class of neural networks with a fractional-order derivative. By using the contraction mapping principle, Krasnoselskii fixed point theorem and the inequality technique, some new sufficient conditions are established to ensure the existence and uniqueness of the nontrivial solution. Moreover, uniform stability of the fractional-order neural networks is proposed in fixed time-intervals. Finally, some examples are given to illustrate the effectiveness of theoretical results.