test

程序主要包括：1．MyInit.m 数据初始化 输出参数： XTrueZ 目标真实轨迹 Z0 目标观测值 T 采样周期 Q 系统误差阵 DeltaR 距离误差 DeltaSita 方位角误差 DeltaBeta 俯仰角误差 totaltime 运动时间 montimes 蒙特卡罗仿真次数 2． EKF.m [Z1]= EKF Z1: 输出EKF滤波后结果 3. CMKF.m [Z2]= CMKF Z2: 输出CMKF滤波后结果 4. GetR.m CMKF算法中误差阵R的计算 5． CompareEandC.m EKF和CMKF、最小二乘滤波后结果比较 部分绘图代码不全，具体结果请参见 信号实验作业.doc 文档 6．source.m 产生带野值的数据 7. RemoveWilddata.m 野值剔除算法 (Procedures will include: 1. MyInit.m initialization data output parameters: XTrueZ target the real target trajectory Z0 sampling period T observed value Q system error array DeltaR distance error DeltaSita azimuth error DeltaBeta pitch angle error totaltime exercise time montimes the number of Monte-Carlo simulation 2. EKF.m [Z1] = EKF Z1: Output EKF filtered results 3. CMKF.m [Z2] = CMKF Z2: Output CMKF filtered results 4. GetR.m CMKF algorithm for the calculation of error R array 5. CompareEandC.m EKF and CMKF, least-squares filtering Comparison of part of the drawing code after the failure, specifically the results of experimental work, see the signal. Doc document 6. source.m generate the data with outliers 7. RemoveWilddata.m outliers removed Algorithm)

姓名管理制度

说明：  使用SVM分类器来预测乳腺癌病人的预后(特征选择；分类器构建)，评价模型时使用无被交叉验证，性能评价指标包括准确率，AUC，灵敏度，特异度。学会最基本的机器学习方法。可查看分发给大家的代码，以后遇到类似的问题，可用相似的思路和代码。(The SVM classifier was used to predict the prognosis of breast cancer patients (feature selection; classifier construction), and the model was used without cross-validation. Performance evaluation indicators included accuracy, AUC, sensitivity, and specificity. Learn the most basic machine learning methods. You can view the code distributed to everyone, and later encounter similar problems, similar ideas and code can be used.)

ASP+Ajax异步请求和获取数据(页面不刷新)的实例，ASP只是后台页面，改成PHP或.net都可以(Creating a two-dimensional code of the middle band web site LOGO through the QRCode class library)

一个简单的猜数游戏，程序自动生成一个一到一百的随机数，6次机会(a simple guess number game)

文件切割，特别对于Email上传文件有用。-paper cutting, especially Email upload documents useful.

this is the source code for the philip model(philip model)

说明：  主要计算了轮轨接触2D算法，是很好的一个程序 简单明了(The 2D algorithm for wheel rail contact is mainly calculated It's a good program to be simple and clear)

基于stm32测试控制变频器控制异步电机(Control asynchronous motor based on STM32 test control frequency converter)

这里实现跑马灯的方法是，依次灭掉前一个灯和点亮后一个灯，再延时一会，不断循环，就可以看到跑马灯的效果了。 请在编译后，进入仿真，点全速运行看结果-Marquee realize here the approach is to eliminate the former followed by a light and lit a lamp post, and then one will be delayed, and constantly cycle, you can see the effect of the Marquee. Please compiled into the simulation, watch the results point to run at full speed