Description: SOFM(自组织特征映射)：这种算法部分收到生物特征影响，在网络输出层内按几何中心或特征进行聚类。-SOFM (self-organizing feature map) : This algorithm received some biological features, the output layer to the network within the geometric center or cluster features. Platform: |
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Author:何风 |
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Description: 开发环境:Matlab 简要说明: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。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method. Platform: |
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Author:李洋 |
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Description: Kohonen的SOFM(自组织特征映射)：这种算法部分收到生物特征影响，在网络输出层内按几何中心或特征进行聚类。-Kohonen the SOFM (self-organizing feature map) : This algorithm received some biological features, the output layer to the network within the geometric center or cluster features. Platform: |
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Author:辜小花 |
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Description: 国外游戏开发者杂志2003年第二期配套代码，包含了Jon Blow的交互工具的版本更新，使用了一个Kohonen Self-Organizing Feature Map来区分系统的行为--Code of game development magazine in 2003 second issue, it including Jon Blow`s version renewal of interactive tool ,it has used Kohonen Self-Organizing Feature Map to differentiate system the behavior Platform: |
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Author:站长 |
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Description: 开发环境:Matlab 简要说明: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。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method. Platform: |
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Author:李洋 |
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Description: Kohonen的SOFM(自组织特征映射)：这种算法部分收到生物特征影响，在网络输出层内按几何中心或特征进行聚类。-Kohonen the SOFM (self-organizing feature map) : This algorithm received some biological features, the output layer to the network within the geometric center or cluster features. Platform: |
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Author:辜小花 |
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Description: 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 basis of a new non-supervised clustering method, analysis based on self-organizing feature map network clustering of the learning process, analyzed the weights of self-organization the process of neighborhood function and learning step-size problem of the general values are given based on the self-organizing feature map network clustering algorithm to achieve concrete and practical examples of tests, confirmed the correctness of the algorithm. Platform: |
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Author:zhaiyaojie |
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Description: 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 Platform: |
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Author:JW |
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Description: 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 sample data SOFMSAMP.PAT. The self-organizing feature map process to accept input vector and calculate the weight of the composition. Output directed to the screen. Platform: |
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Author:刘柳 |
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Description: 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，获胜节点及其周围节点的连接权矢量向输入模式的方向作相应的修正。当输入模式类别发生变化时，二维平面上的获胜节点也从原来节点转移到其它节点。这样，网络通过自组织方式用大量训练样本数据来调整网络的连接权值，最后使得网络输出层特征图能够反映样本数据的分布情况。根据SOM网络的输出状况，不仅能判断输入模式所属的类别，使输出节点代表某类模式，而且能够得到整个数据区域的分布情况，即从样本数据得到所有数据的分布特征。 -SOM neural network (self-organizing feature map neural network) is an unsupervised neural network. Network topology is an input layer and an output layer. Input layer nodes is the input dimension of the sample, each node represents a component input samples. Output layer nodes are arranged in two-dimensional array structure. X in the input layer and output layer each node of each neuron node Y by a weight (the weight vector as W) is connected, so that each output layer corresponds to a connection node of the right vector.
Self-organizing feature maps of the basic principle is, when each category of inputs into the model, its output layer one node get the maximum boost and win, Huoshengjiedian around Yixiejiedian Yin Zuo Yong Ye Shoudaojiaotai lateral stimulation. Then a learning network operation, the winner node and surrounding nodes in the right direction vector to the input mode to make consequential amendments. When the input mode type changes, the two-dimensional plane of the wi Platform: |
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Author:leidan |
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Description: 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,including a paradigm of SOFM implemented
in Matlab,analyzed the problem of SOFM at present and prospected its researching trend in the future.
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Author:dreamer |
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Description: 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. Platform: |
Size: 1024 |
Author:yyt |
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Description: 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. Platform: |
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Author:Mulyanto |
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Search - self organizing feature map