模糊逻辑神经元研究进展

Research progress of fuzzy logic neurons

模糊逻辑神经元作为模糊神经网络的重要组成部分,一直以来备受关注,从模型设计到算法研究,成果颇多。以往的研究多集中于模糊逻辑神经元在某一方面的应用模型、性质和算法,具有突出的针对性和特殊性;而今的研究多立足于构造一种能够包容各种逻辑形态的通用神经元,以体现思维的灵活性和多样性,进而提高神经元的推广和应用价值。针对当前模糊逻辑神经元的研究进展做了综述,分析了前后两类不同模型的典型结构及特点,并明确了未来的发展方向。

Fuzzy logic neurons have received much concern all the time as the important components of fuzzy neural networks. From models designing to algorithms studying, there are many achievements. Past research more concentrated on application models, properties and algorithms of fuzzy logic neurons in a certain aspect, and had outstanding pertinence and particularity. Current research is more established in constructing a kind of universal neurons which contain all of different logic forms, in order to reflect flexibility and diversity of thinking. And then the value of popularization and application of neurons is improved. A survey to research progress on fuzzy logic neurons at present is made. The typical structures and characteristics of the two classes of different models altogether are analyzed, and the orientation of the research is clarified.