模糊ARTMAP神经网络在一维信息聚类分析中的应用  

THE FUZZY ARTMAP NEURAL NETWORK'S APPLICATION IN ANALYZING ONE DIMENSIONAL SIGNALS

作　　者：秦安文[1] 

机构地区：[1]山东工业大学电力工程学院,济南250061

出　　处：《山东工业大学学报》1999年第5期490-496,共7页

摘　　要：从生物脑神经网络的信息处理入手，讨论了ＡＲＴＭＡＰ人工神经网络的聚类模型，给出了其有师学习过程，并依据物以类聚的哲学原理，从类的角度，论述了事物细节的类可描述性，为一维信息的描述提供了新的途径． 同常规的数学关系描述法相比，对于那些无法用确定的数学模型来描述的事件信息，类描述法有其独到之处．The author of the paper, by analyzing the message processes of the brain neural network, introduces the architecture of the fuzzy ARTMAP neural network and its learning steps. Also based on the point of the materalism that things come together with their common qualities, he thinks that we can describe things into classifications. Morever, he provides a new method for analyzing one dimensional signals. Compared with mathematic relations we usually use, this method is very useful for those signals which can not be analyzed by a certain mathematic model.

关 键 词：神经元模型 类分离程度 激励 模糊ARTMAP神经网络 一维 信息 聚类分析 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]