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一个自组织映射的很好的程序,其中包含4个演示程序,使用者也可以在此基础上进行开发,很方便的。-a Self-Organizing Map of good procedures, which include four demo program, users can also conducted on the basis of this development, is very convenient.
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基于自组织特征映射网络的聚类分析,是在神经网络基础上发展起来的一种新的非监督聚类方法,分析了基于自
组织特征映射网络聚类的学习过程,分析了权系数自组织过程中邻域函数和学习步长的一般取值问题,给出了基于自组织
特征映射网络聚类实现的具体算法,并通过实际示例测试,证实了算法的正确性。
-Based on self-organizing feature map network cluster analysis, neural network is developed on the basi
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基于自组织特征映射(SOM)的系统辨识算法实现-Based on self-organizing feature map (SOM) of the system identification algorithm
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MATLAB implementation of time series prediction Based on the VQTAM method described in the following papers:
G. A. Barreto & A. F. R. Araujo (2004)
"Identification and Control of Dynamical Systems Using the Self-Organizing Map"
IEEE Transac
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该目录包含了代码执行Kohonen自组织特征
地图网络。源代码中可以找到SOFM.CPP 。样本数据中发现
SOFMSAMP.PAT 。的自组织特征映射程序接受输入的载体和组成
计算重量。输出定向到屏幕上。-This directory contains the code to implement Kohonen self-organizing feature map network. Source code can be found SOFM.CPP. Found in the s
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This code is the implementation of Mahalnobis SOM algorithm published in this article.
Face recognition under varying illumination using Mahalanobis self-organizing map
S Aly, N Tsuruta, RI Taniguchi - Artificial Life and Robotics, 2008 - Springe
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Neural Network Based Clustering
using Self Organizing Map (SOM) in Excel
Here is a small tool in Excel using which you can find clusters in your data set. The tool uses Self Organizing Maps (SOM) - originally proposed by T.Kohonen as the metho
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MATLAB的自组织映射神经网络源码和相应的实验数据-MATLAB' s self-organizing map neural network source code and the corresponding experimental data
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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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ANN Simulink/Matlab. Constructing Kohonen Self-Organizing-Map (SOM)
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量子自组织特征映射网络聚类算法仿真程序
量子群智能优化算法-Quantum self-organizing feature map network clustering algorithm simulation program
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SOFM网络及其在MATLAB中的实现.本文详细叙述了自组织映射网络的原理、算法及其在
Matlab中实现的工具箱,并结合实例给出了SOFM在Matlab上的实现方法,对于SOFM的现存问题和未来研究趋势作了分析和展望。
-This paper described the principle,the algorithm andthe toolbox in Matlab of Self-organizing Feature Map Neural Network detailedly,inc
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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 n
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自组织映射神经网络是一类新异类分类方法,可以较好的解决一类分类问题!-The self-organizing map neural network is a new class of heterogeneous classification, a classification can be a better solution!
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MATLAB' s self-organizing map neural network source code and the corresponding experimental data
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self organizing map Kohonen Neural Network
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Self Organizing Map example in MATLAB
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Self Organizing Map MATLAB code
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self-organizing map neural network source
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Use the SOM for clustering data without knowing the class memberships of the input data. The SOM can be used to detect features inherent to the problem and thus has also been called SOFM, the Self-Organizing Feature Map.
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