Input-Output Stability for Differential Neural Networks

This paper deals with the problem to obtain inputoutput stability for a certain class of differential neural networks. Hence, by using a Lyapunov function, the conditions to guarantee finite-gain $\L$-stability, which also ensures global exponential stability (GES), are established. Finally, the simulation of a numerical example illustrates the applicability of this approach.