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Self-organizing_feature_map_model

于 2010-12-11 发布 文件大小:1KB
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  自组织特征映射模型(Self-Organizing feature Map),认为一个神经网络接受外界输入模式时,将会分为不同的区域,各区域对输入模式具有不同的响应特征,同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激,而较远的神经元则相互抑制,更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。(Self-organizing maps model (Self-Organizing feature Map), that a neural network to accept outside input mode, will be divided into different regions, the regional input modes have different response characteristics, while the process is done automatically . The connection weights of neurons with a certain distribution. Nearest neurons stimulate each other, while distant neurons are mutually inhibitory, with a further some of the weaker stimulus. Self-organizing feature map method is a clustering method without teachers.)

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