A Highly Accurate Robust BP-fuzzy Reasoning System for Learning Combination
高精度RBP-模糊推理复合学习系统

A new accurately robust BP-fuzzy reasoning system for learning combination is proposed. This learning system is mainly constructed with a robust BP network with fuzzy reasoning which replaced robust estimation and mixed fuzzy reasoning. The main feature of this learning system is a simple algorithm constructed from the following three parts: RBP learning algorithm, max-min fuzzy reasoning and rain-max fuzzy reasoning. This learning system is applied to a target tracking problem. The results of test show that this tracking system is more accurate and more robust.