Description: 自组织系统Kohonen网络模型。对于Kohonen神经网络,竞争是这样进行的:对于“赢”的那个神经元c,在其周围Nc的区域内神经元在不同程度上得到兴奋,而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程,经过一定次数的训练以后,网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构:它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ .. Platform: |
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Author:张洁 |
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Description: 自组织 Kohonen 映射程序,当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。 -Kohonen self-organizing map process, when a neural network to outside input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is done automatically. 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: |
Size: 4096 |
Author:yybb |
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Description: 自组织系统Kohonen网络模型。对于Kohonen神经网络,竞争是这样进行的:对于“赢”的那个神经元c,在其周围Nc的区域内神经元在不同程度上得到兴奋,而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程,经过一定次数的训练以后,网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构:它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ .. Platform: |
Size: 34816 |
Author:张洁 |
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Description: 神经网络源码可应用于遥感图像分类,包括bp、kohonen等方法-neural network source can be used in remote sensing image classification, including bp, Kohonen methods Platform: |
Size: 4096 |
Author:刘武 |
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Description: matlab的详细手册(中英文版)、matlab的相关程序实例、用maple和matlab解决科学计算问题的资料
Kohonen网络的模式识别和LVQ神经网络的模式识别-matlab detailed manual (in English), matlab examples of the relevant procedures, using maple and matlab to solve issues in scientific computing Kohonen network LVQ neural network pattern recognition and pattern recognition Platform: |
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Author:lbj |
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Description: 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 method for clustering.
* Neural Network based Clustering tool in Excel (209 KB in Zipped format. 947 KB when unzipped.)
Inside the downloaded zip file, you will find the Excel file containing the application. Before running it, I suggest that you go through the ReadMe worksheet. It contains brief instructions on how to run the tool.
If you are interested in building Prediction and Classification models in Excel using Feedforward-Backpropagation Neural Network, here are two small Excel based tools for you. Also, if you are interested in Tree based Classification models, here is a Tree based classifier in Excel.
-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 method for clustering.
* Neural Network based Clustering tool in Excel (209 KB in Zipped format. 947 KB when unzipped.)
Inside the downloaded zip file, you will find the Excel file containing the application. Before running it, I suggest that you go through the ReadMe worksheet. It contains brief instructions on how to run the tool.
If you are interested in building Prediction and Classification models in Excel using Feedforward-Backpropagation Neural Network, here are two small Excel based tools for you. Also, if you are interested in Tree based Classification models, here is a Tree based classifier in Excel.
Platform: |
Size: 214016 |
Author:Jessie |
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Description: pdf for fingerprint from ieee include:
PIPELINED MINUTIAE EXTRACTION FROM FINGERPRINT IMAGES
A Novel Principal Component Analysis Neural Network Algorithm for Fingerprint Recognition
in Online Examination System
Processing of Distorted Fingerprints with use of Three-Rate
Hybrid Kohonen Neural Networks
nad etc Platform: |
Size: 21190656 |
Author:ali |
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Description: 人工神经网络SOM,通过输入训练样本,训练次数等参数进行训练,实现模式分类-Artificial neural network SOM, by entering the training sample, training times and other parameters of training to achieve pattern classification Platform: |
Size: 267264 |
Author:苏米 |
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Description: Kohonen神经网络算法工作机理为:网络学习过程中,当样本输入网络时,竞争层上的神经元计算输入样本与竞争层神经元权值之间的欧几里德距离,距离最小的神经元为获胜神经元。调整获胜神经元和相邻神经元权值,使获得神经元及周边权值靠近该输入样本。通过反复训练,最终各神经元的连接权值具有一定的分布,该分布把数据之间的相似性组织到代表各类的神经元上,使同类神经元具有相近的权系数,不同类的神经元权系数差别明显。需要注意的是,在学习的过程中,权值修改学习速率和神经元领域均在不断较少,从而使同类神经元逐渐集中。-Kohonen neural network algorithm for the working mechanism: the network learning process, when the samples enter the network, the competitive layer of neurons on the calculation of input samples and competitive layer neurons Euclidean distance between the weights from the smallest neurons Winning neuron. Adjust the winning neuron and neighboring neurons weights to gain weight and peripheral neurons close to the input samples. Through repeated training, and ultimately the connection weights of neurons with a certain distribution, the distribution of the similarity between the data to representatives of organizations of various types of neurons, so that similar neurons have similar weights, different types of nerve Element obviously different weights. Note that, in the learning process, the right to modify the value of the field of learning rate and neurons were constantly low, so that the same neurons gradually concentrated. Platform: |
Size: 87040 |
Author:李芳 |
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Description: 神经网络源码,可应用于遥感图像的分类,采用的包括bp、kohonen。可以作为范例来学习。-Neural network source code can be used in remote sensing image classification, using the included bp, kohonen. Can serve as examples to learn. Platform: |
Size: 5120 |
Author:葛宏 |
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Description: 这是有关神经网络算法中的kohonen算法的代码实现和有关介绍文章。共大家参考。是本人自己做的程序。虽然是比较旧的算法。但对新学神经网络的朋友会有所帮助。-This is the neural network algorithm kohonen algorithm code and the introduction article. Of reference. Is my own program. Although the older algorithm. But the new study neural network of friends will help. Platform: |
Size: 2392064 |
Author:ANMINGSHOU |
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Description: 这是一个关于Kohonen神经网络的小程序,主要实现了利用神经网络进行聚类的功能,经测试具有良好效果-This is a small program on Kohonen neural network, the main achievement of the neural network clustering feature has been tested with good results Platform: |
Size: 87040 |
Author:张甬力 |
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