We demonstrate the use of neural networks to model the attractors of musical instruments from time series. We show how the neural networks have to be extended to be able to model instationary behavior. To give an impression of the use of the models we summarize some results of analyzing the instrument dynamics and we show that the neural models are stable in the sense that they allow resynthesis of natural sounds.