高精度RBP-模糊推理复合学习系统
A Highly Accurate Robust BP-fuzzy Reasoning System for Learning Combination
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摘要: 该文提出了高精度RBP-模糊推理复合学习系统.系统主要由基于鲁棒估计的鲁棒BP 学习环节和基于混合合成推理的模糊推理环节构成.该学习系统的主要特点是可由鲁棒BP 算法和min-max,max-min模糊推理算法简单地实现.最后通过在目标跟踪问题中应用结 果,表示了该算法的高精度和鲁棒性.Abstract: 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.
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Key words:
- BP network /
- fuzzy reasoning /
- robust estimator /
- target tracking system
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