Normalized Exponential Neural Networks

In this paper, the normalized exponential neural network (ENN) is studied. It is proved that ENN is a universal approximator. The stability relation between systems and neural networks working as controllers is investigated. The results show that when designing a system, one should firstly consider system stability rather than controller stability. Accordingly, a new hybrid learning algorithm is presented, and it is proved that this algorithm eventually converge to equilibria.