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: |
Size: 1024 |
Author:李洋 |
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Description: 一个基于K均值聚类的ＲＢＦ神经网络，注释写的很明白，有不明白的地方可以发邮件问我。-a K-means clustering based on the RBF neural network, notes written very well, did not understand the local mail can ask me. Platform: |
Size: 2048 |
Author:bruce |
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Description: 用matlab编写的聚类rbf神经网络曲线拟和程序。转载的，效果不错。-prepared using Matlab Clustering rbf neural network and curve-fitting procedures. Reproduced in the good results. Platform: |
Size: 1024 |
Author:gwg |
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Description: 本工具包主要是为对神经网络有兴趣人士提供的一种方便，灵活的学习和研究软件。
JNNT由java语言写成，具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览器就可以运行，无需安装任何大型附加软件。更方便爱好者通过internet远程访问资源。
支持反向传播算法(BP),LBG聚类法和径向基网络(RBF)
-This toolkit is for people interested in neural networks has provided a convenient, flexible learning and research software. JNNT by the java language, cross-platform with superior performance. Java applet demo version is more simple to just any machine can run a browser, without installing any large-scale add-on software. Enthusiasts through the internet more convenient remote access to resources. To support the back-propagation algorithm (BP), LBG clustering method and radial basis function network (RBF) Platform: |
Size: 32768 |
Author:林盈 |
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Description: 神经网络中的K均值聚类算法II：
1.KMIn为输入数据文本，其中，第一个参数为所要聚类点个数，第二个参数为聚类点的维数,第三个参数为所要求聚类的个数
2.KM2OUT为经过K均值聚类算法II计算后得到的结果-Neural network in K-means clustering algorithm II: 1.KMIn input data for the text, of which the first parameter to be the number of clustering points, the second parameter is the dimension of clustering points, the third parameter for the clustering the number of requests for 2.KM2OUT after K-means clustering algorithm II calculation results Platform: |
Size: 277504 |
Author:blue8202 |
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Description: 本文的题目是基于分形和遗传算法的人脸识别方法，对有限人群提出一种采用分形特征和遗传聚类的识别方法: 将图像分成很多小区域, 分别计算各个区域的分形特征, 以充分利用图像二维信息 同一个模式有多个样本, 通过遗传算法进行聚类以得到最优解实现不变性识别. 最后采用ORL 人脸图像库的一组图像对比了新方法、本征脸法和自联想神经网络方法, 结果表明该方法的识别率, 与本征脸法相似, 比自联想神经网络高.-The title of this article is based on fractal and genetic algorithms for face recognition method, a crowd of limited use of fractal characteristics and the identification of genetic clustering methods: the image is divided into many small regions, each region were calculated fractal characteristics, to take full advantage of two-dimensional image information with a model for a number of samples, through the genetic clustering algorithm in order to obtain the optimal solution to achieve invariant recognition. Finally, using ORL face image database of a group of image contrast of the new methods, eigenface law and auto-associative neural network methods, results show that the method of recognition rate, with the eigenface method is similar to auto-associative neural network than high. Platform: |
Size: 380928 |
Author:阳关 |
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Description: som 神经网络 分类小例 （将八组4维数据聚类）-som neural network classifier in small cases (eight groups will be 4-dimensional data clustering) Platform: |
Size: 1024 |
Author:姜波 |
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Description: 图像聚类程序源码，运行正常，能实现数字图像、图形的聚类；同时，还采用了多种方法实现，有距离法，神经网络法等，值得参考-Image source clustering procedures, operating normally, to achieve digital images, graphics cluster At the same time, also adopted a number of ways to achieve, a far cry from the law, such as neural network, it is also useful Platform: |
Size: 225280 |
Author:陈艳平 |
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Description: 这是一个用RBF神经网络实现的一个聚类算法，希望能够有用-This is a RBF neural network using a clustering algorithm to achieve the hope of useful Platform: |
Size: 1024 |
Author:lyulong |
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Description: 聚类是把一组个体按照相似性归成若干类别，即“物以类聚”。它的目的是使得属于同
一类别的个体之间的距离尽可能的小而不同类别上的个体间的距离尽可能的大。聚类方
法包括统计方法、机器学习方法、神经网络方法和面向数据库的方法。
-Clustering is a group of individuals as to the similarity in accordance with a number of categories, that is, " 物以类聚." Its purpose is to allow individuals fall into the same category as far as possible the distance between the different categories of small and the individual as much as possible the distance between the major. Clustering methods, including statistical methods, machine learning, neural network methods and database-oriented approach. Platform: |
Size: 1422336 |
Author:qingpeng yu |
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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: 模糊聚类虽然能够对数据聚类挖掘，但是由于网络入侵特征数据维数较多，不同入侵类别间的数据差别较小，不少入侵模式不能被准确分类。本案例采用结合模糊聚类和广义神经网络回归的聚类算法对入侵数据进行分类。
-Although fuzzy clustering to cluster the data mining, but the characteristics of the network intrusion data more dimensions, different invasion was little difference between categories of data, many intrusion model can not be accurately classified. This case using fuzzy clustering and generalized regression neural network clustering algorithm to classify data on the invasion. Platform: |
Size: 25600 |
Author:si |
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Description: 用matlabr2009编程实现神经网络模糊聚类算法，采用cell工具把整个程序分为以下几个部分-Programming neural network with matlabr2009 fuzzy clustering algorithm, using cell tools to the entire program is divided into the following sections Platform: |
Size: 1024 |
Author:霸王仔 |
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