Stable fourier neural networks with application to modeling lettuce growth

In general, neural networks cannot match non-linear systems exactly. Neuro identifier has to include robust modification in order to guarantee Lyapunov stability. In this paper input-to-state stability approach is applied to access robust training algorithms of Fourier neural network (FoNN). It is successfully applied on modeling lettuce growth in green-house.