freq-filters

HSQARKH 完整源码，这只是一个初步代码,用来实现ARK,做隐藏方面研究的. (HSQARKH complete source code, this is just a preliminary code that is used to achieve ARK, so hidden aspects of the study.)

randgen(mu,mu1,mu2,cov1,cov2,cov3) = Random generation of Gaussian Samples in d-dimensions where d = 2 mu, mu1, mu2 = (x,y) coordinates(means) that the gaussian samples are centered around cov1, cov2, cov3 are the covariance matrices and will vary changing the shape of the distribution, example: cov = sigma^2*Identity Matrix, where sigma^2 = a scalar N = the number of gaussian samples used are provided as user input, A test set of N/2 and a training set of N/2 gaussian samples is also generated Output is directed to the command window and a plot of the distributions are generated

使用matlab实现电子波动性和粒子性的演示(Use matlab electronic fluctuations and particle demo)

It is the corresponding testing module of the function that is specified in the training phase. test_set is a NxD matrix where N is the number of samples in the test set and D is the dimension of the feature space. true_labels is a Nx1 matrix specifying the class label of each corresponding sample s features (each row) in test_set . adaboost_model is the model that is generated by the function ADABOOST_tr .

包含单缝衍射，光栅衍射，等倾干涉，等厚干涉，杨氏双缝干涉，菲涅耳衍射等基础函数(Contains a single-slit diffraction, diffraction grating, equal inclination interference, equal thickness interference, Young' s double slit interference, Fresnel diffraction and other basic functions)

一种IMC与PID组合控制的实现，提供matlab源码实现，及simulink实现。(IMC and PID.)

Unscented Kalman Filter and Extended Kalman Filtering Tutorial and source code, includes worked examples and source.

我自己编写的简单的nsga2程序，对于初次接触该算法的朋友会有很大帮助(I have written a simple nsga2 program will be very helpful for the initial contact with the friends of the algorithm)

Dreamweaver_CS5官方教程,帮助您快速掌握相关知识，好用(Dreamweaver_CS5 official tutorial to help you quickly master the relevant knowledge, easy to use)

粗大误差判别，系统误差和随机误差的计算，对于初学者非常有用(Calculate gross error identification, systematic error and random error, very useful for beginners)