Self-Organizing Feature Map Neural Networks (SOM) SOM是一种无监督学习的神经网络,先贴上最近写的一个利用SOM对图片进行压缩并恢复的简单应用,留个大坑:1.有空再来总结SOM的概念,学习过程,优化算法。2.把代码再用python和C++重新实现一遍作为编程练习。。。 训练过程大致如下: 将图片分解并形成输入向量X = {...
The default learning in a self-organizing feature map occurs in the batch mode (trainbu). The weight learning function for the self-organizing map is learnsomb. First, the network identifies the winning neuron for each input vector. Each weight vector then moves to the average position of all...
Self-organizing feature map neural network classification of the ASTER data based on wavelet fusion[J] . Bagan Hasi,Jianwen Ma,Qiqing Li,Xiuzhen Han,Zhili Liu.Science in China Series D: Earth Sciences . 2004 (7)Bagan;Hasi;Jianwen;Ma;Qiqing;Li;Xiuzhen;Han;Zhili;Liu.Self-organizing feature ...
Self-Organizing Map Neural Network 類神經網路 Self-Organizing Map Neural Network 陳慶瀚 義守大㈻電機系 2002年3㈪20㈰
自组织网络模型(Self-organizing Neural NetWork):Kohonen的自组织特征映射神经网络(seIf-organizing Feature Map)。自组 …www.cnblogs.com|基于6个网页 2. 自组织神经网络 自组织竞争神... ... ) self-organizing competitive network 自组织竞争网络 ) self-organizing neural network 自组织神经网络 ... www....
A self-organizing feature map is defined as a neural network technique that captures the topology and probability distribution of input data by updating the weight matrix based on a bi-dimensional Gaussian function during the training stage.
A global path planning method using self-organizing feature map which is a method among a number of neural network is presented. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron,...
Self-organizing map (SOM), an unsupervised learning way of artificial neural network, plays a very important role for classification and clustering of inputs. The property of SOM, also called topology-preserving maps or self-organizing feature map (SOFM), is observed in human brain which is not...
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6. Repeat step 2 until the map has converged. 3. Two phases of the adaptive process 1. The First Phase An ordering or self-organizing phase The ordering phase may take as many as 1000 iterations and possibly more. The learning rate should begin with a value close to 0.1; there after ...