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SOM神经网络（自组织特征映射神经网络）是一种无导师神经网路。网络的拓扑结构是由一个输入层与一个输出层构成。输入层的节点数即为输入样本的维数，其中每一节点代表输入样本中的一个分量。输出层节点排列结构是二维阵列。输入层X中的每个节点均与输出层Y每个神经元节点通过一权值(权矢量为W)相连接，这样每个输出层节点均对应于一个连接权矢量。
自组织特征映射的基本原理是，当某类模式输入时，其输出层某一节点得到最大刺激而获胜，获胜节点周围的一些节点因侧向作用也受到较大刺激。这时网络进行一次学习操作，获胜节点
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无导师学习神经网络的分类——矿井突水水源判别-Unsupervised learning neural network classification- mine water inrush discrimination
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无监督神经网络利用matlab能够有效的实现图像化，还能得到最有结果-Unsupervised neural network using matlab can effectively realize the image of, but also get the most results
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自组织特征映射神经网络是一类无导师学习的神经网络模型可用于聚类分析-Self-organizing neural network is a kind of unsupervised learning neural network model can be used for cluster analysis
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An important aspect of an ANN model is whether it needs
guidance in learning or not. Based on the way they learn, all
artificial neural networks can be divided into two learning
categories - supervised and unsupervised.
• In supervised l
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无导师学习神经网络的分类——矿井突水水源识别matlab程序-Categories unsupervised learning neural networks- mine water bursting source identification matlab program
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Self-Organizing Incremental Neural Network is an
Neural Network model for incremental or on-line
learning. It is proposed by Dr. Furao Shen and Osamu
Hasegawa in 2006: Shen Furao & Osamu Hasegawa, "An
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