Asproximation of Hybrid Systems by Neural Networks

摘要

In this paper it is shown that hybrid systems can be approximated arbitrarily well by recurrent neural networks. The results indicate that the newly emerging field of hybrid systems can be considered in terms of the architectures and learning algorithms developed for neural nework models. Examples are given of the types of architectures that can be developed.