capon

高准确度,支持50Hz/60Hz IEC 687/1036 标准的准确度要求,在500:1 的动态范围内误差小于0.1 (High accuracy, supports 50Hz/60Hz IEC 687/1036 standard accuracy requirements, the 500:1 dynamic range of error is less than 0.1 )

前面搞错了,把五个文件一起打包上传了,现在一个一个传 考尔Cauer滤波器的离散滤波算法 模拟程序 程序头上有详细的注释和使用说明(Made a mistake in front of the pack with five file upload, and now one by one Chuan Kaul Cauer filter discrete filtering algorithm simulation program procedures detailed head notes and use)

用有限差分法来解偏微分方程，采用高斯——赛德尔迭代方法，并用前后两次迭代差的矩阵的无穷范数作为是否停止迭代的依据。(Using finite difference method to solve partial differential equations, using Gauss- Seidel iterative methods, and poor before and after the two iterations of the infinite matrix norm as the basis of whether or not to stop iteration.)

这是在MATLAB下写的一段程序是个时钟动画,很有意思,可以从中领悟如何在MATLAB下来编写程序(This is in the Writing section of MATLAB procedures under the clock are animation, very interesting, can understand how to down MATLAB programming)

基于MATLAB的LDPC码编译设计，是ＬＤＰＣ的基础程序，适合初学者(MATLAB-based LDPC code compiler design is based LDPC program, suitable for beginners)

说明：  MATLAB在信号处理中的应用 3 傅里叶(Fourier)变换 IIR数字滤波器的设计方法 FIR数字滤波器设计(MATLAB in signal processing of the application of three Fourier (Fourier) transform the design method of IIR digital filter FIR digital filter design)

A gui software for developing GUI in Matlab.

AdaBoost元算法属于boosting系统融合方法中最流行的一种，说白了就是一种串行训练并且最后加权累加的系统融合方法。 具体的流程是：每一个训练样例都赋予相同的权重，并且权重满足归一化，经过第一个分类器分类之后， 计算第一个分类器的权重alpha值，并且更新每一个训练样例的权重，然后再进行第二个分类器的训练，相同的方法....... 直到错误率为0或者达到指定的训练轮数，其中最后预测的标签计算是各系统*alpha的加权和，然后sign（预测值）。 可以看出，训练流程是串行的，并且训练样例的权重是一直在变化的，分错的样本的权重不断加大，正确的样本的权重不断减小。 AdaBoost元算法是boosting中流行的一种，还有其他的系统融合的方法，比如bagging方法以及随机森林。 对于非均衡样本的处理，一般可以通过欠抽样(undersampling)或者过抽样(oversampling)，欠抽样是削减样本的数目， 过抽样是重复的选取某些样本，最好的方法是两种进行结合的方法。 同时可以通过删除离决策边界比较远的样例。 (AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative. Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way ....... 0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value). As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing. AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method. For )

利用云模型实现评估功能，包括标准云的绘制和生成，入门的通知们可以看下啦(Cloud model implementation uation features, including standard cloud rendering and generation, introductory notice can look it)

说明：  使用PSO优化SVR支持向量机模型的代码，有详细的输出及输出，以及代码说明(Use PSO to optimize SVR support vector machine model code, with detailed output and output, as well as code description)