This paper presents a new parameter and confidence estimation techniques for dynamic GMDH neural networks. The main objective is to show how to employ the bounded error approach to solve such a challenging task that occurs in many practical situations. In particular, the proposed approach can be easy applied in robust fault detection schemes.
