shaoshao

说明：  一个非常优秀的BP神经网络Matlab源程序(A very good BP Neural Networks Matlab source code)

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简单来说，卡尔曼滤波器是一个"optimal recursive data processing algorithm（最优化自回归数据处理算法）"。对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。(In short, the Kalman filter is an " optimal recursive data processing algorithm (optimal autoregressive data processing algorithm)." For most of the problems to solve it, he is the best, most efficient or even useful.)

Elman neural network prediction Mackey-Glass serie

piano contpue detection - image processing

模糊核聚类算法的几篇论文及matlab源码，可以以练代学，更好掌握模糊聚类方法。(Fuzzy Kernel Clustering Algorithm matlab several papers and source code, can be practicing on behalf of science, to better grasp the fuzzy clustering method.)

图像特征提取以及匹配，sift代码。可用于图片检索中，同比SURF，其算法可以较好的识别图像中文字(Image feature extraction and matching, sift the code. Can be used for image retrieval, up by SURF, the algorithm can better identify the image text)

描述了一个用matlab描述的卡尔曼滤波实现的例子，可以直接运行观察结果，对kalman滤波的学习有很好的借鉴作用(Describes a Kalman filter is described by matlab examples of implementation can be run directly observe the results of the kalman filter has a good reference for learning)

说明：  matlab sdr model works awesome

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 kinds of clustering algorithms source code and sample code, the ultimate goal of this program is to form a set of standards for clustering, scalable tools. Including the contents of a. Clustering algorithm: Kmeans and Kmedoid algorithms, FCMclust, GKclust, GGclust algorithm 2. Assessment classified prototypes: programs can be plotted in two-dimensional image, the results of clustering 3. Verify: Program to provide an algorithm to each authentication mechanism, each clustering algorithm will calculate 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 metrics.)