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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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神经网络实例集。包括以下几个程序单层线性神经网络实例、感知器神经元解决较复杂输入向量的分类问题、基于感知器神经网络处理复杂的分类问题、数值分析程序matlab-GUI、用BP网络完成函数的逼近源程序、自组织特征映射应用实例-Examples of neural network sets. Procedures include the following examples of single-layer linear neural network, perceptron neuron input
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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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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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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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som matlab source code from http://chi3x10.wordpress.com/2008/05/08/som-self-organizing-map-code-in-matlab/
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在matlab环境中自动识别连通区域的大小,迭代自组织数据分析,感应双馈发电机系统的仿真,调试通过可以使用,通过虚拟阵元进行DOA估计,最大似然(ML)准则和最大后验概率(MAP)准则。-Automatic identification in the matlab environment the size of the connected area, Iterative self-organizing data analysis, Simulation of doubly fed inducti
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In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing M
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SOM example in MATLAB
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Self Organizing Map example in MATLAB
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SOM Neural Network example in MATLAB
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Color Reduction and Quantization using k-Means, Fuzzy Clustering (FCM), and SOM Neuarl Network in MATLAB
In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent c
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