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MATLAB5.X应用与技巧也是一本比较老的关于MATLAB的教材，虽然是比较老版本的，但也有很好的指导做用(MATLAB5.X applications and skills is a relatively old on MATLAB materials, although the old version, but there are also a good guide to do with)

Please send to you my code matlab example

四种聚类算法源代码及示例代码,本程序的最终目的是形成一套标准的用于聚类、可扩展的工具。包括的内容有1. 聚类算法：Kmeans和Kmedoid算法、FCMclust, GKclust, GGclust算法 2. 评估分类原型：程序可以在二维图像上绘制出聚类的结果 3. 验证：程序给每一个算法提供验证机制，每个聚类算法会统计Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), Separation Index (S), Xie and Beni s Index (XB), Dunn s Index (DI) and Alternative Dunn Index (DII)几种衡量指标。(Four clustering algorithm source code and sample code, the ultimate goal of this process is the formation of a set of criteria for clustering, scalable tool. Including the contents of 1. Clustering Algorithm: Kmeans and Kmedoid algorithm, FCMclust, GKclust, GGclust algorithm 2. Assess the classification of a prototype: The procedure can be two-dimensional images to map out the results of clustering 3. Verify: Program to provide every algorithm authentication mechanism, each clustering algorithm statistics Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), Separation Index (S), Xie and Beni s Index (XB), Dunn s Index (DI) and Alternative Dunn Index (DII) of several indicators.)

In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.

stats 用于检验回归模型的统计量，有三个数值：相关系数r2、F值、与F对应的概率p.相关系数r2越接近1，说明回归方程越显著；F > F1-α（k，n-k-1）时拒绝H0，F越大，说明回归方程越显著；与F对应的概率p 时拒绝H0，回归模型成立.(stats for the test statistic of the regression model, there are three values: the correlation coefficient r2, F value, and F corresponds to the probability p. The correlation coefficient r2 more close to 1, note the more significant regression equation F> F1-α (k, nk-1) refused to H0, F the bigger shows the more significant regression equation F corresponds with the probability p refused H0, set up a regression model.)

曲线的卡尔曼滤波程序仅供参考。谢谢大家的支持。要是好的话多支持我啊(good)

mimo信道容量的matlab的分析mimo信道容量的matlab的分析mimo信道容量的matlab的分析mimo信道容量的matlab的分析(MIMO channel matlab)

使用迭代法，用Matlab模拟方形镜自在模的形成过程(Using iterative method , Matlab simulation square mirror the formation process of mould at ease )

its used to remove haze..

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