LMS自适应滤波C程序，语音降噪的

cp2104的老驱动不支持win10，折腾了好一会儿，网上的很多连接都是假的，本资源亲测可用。

经本人测试通过，可以运行，人脸检测人脸识别效果都很好，可以用于毕业设计，一个完整的人脸识别系统源代码，经本人测试通过，可以运行，人脸检测人脸识别效果都很好，可以用于毕业设计，一个完整的人脸识别系统源代码，经本人测试通过，可以运行，人脸检测人脸识别效果都很好，可以用于毕业设计，一个完整的人脸识别系统源代码，

Simplorer V9的培训资料，非常详细，一共407页的PDF，看完这个PDF，相信你已经是simplorer高手了。Conventions Used in this GuideGetting HelpAnsoft Technical SupportHelp MenuContext-Sensitive Help1. IntroductionOverview of the Simplorer Interface .........1-32. Creating a New ProjectAbout the three-Phase rectifier2-2Expected Results2-3Using Simplorer to Create and Improve the Design2-4Creating the new project2-5Add the New project2-5Rename the designAdd Design Notes(Optional)Save the New project2-73. Create the rectifier modelCreate the Three-Phase rectifier Schematic. 3-2Choosing, Placing, and Arranging Components onthe schematic she.3-3Connecting the Components3-8Defining Component Properties3-9Property Displays for Components3-13Specifying simulation Outputs.3-16Defining Solution Options and Analysis Parameters3-18Starting an Analysis3-19Plotting Rectifier Model Simulation Results3-204. Hysteresis Current-Controlled DC-Motor Start-UpModify the Rectifier Model Design.4-2Deleting the Resistive/Inductive Load,4-3Saving the sheet with a New Name4-3Place and Arrange the New Components4-4Connect the New Components.,,,,,,4-5Defining dc Machine valuesDefining Mechanical Load4-7Freewheeling Diode4-8Chopper Transistor4-8Controller Modeling using block elements..4-9Modifying Report Elements...4-11Display Diode CharacteristicDefining Simulation Parameters.4-13Starting Simulation(Block Components.4-13Simulation Results(Block Components)... 4-14Controller Modeling Using State Graph Components4-15Connecting the State Graph Components4-16Defining Properties of State Graph Components 4-Using Name References4-19Deactivating Components on the sheet4-19Starting Simulation(State Graph)...4-21Simulation Results(State Graph)4-225. Current and Speed Controlled Dc MotorModify the State graph design5-2Deleting the State GraphSaving the sheet with a New namePlacing and Arranging the New Block Componentson the sheet5-4Connecting the New ComponentsDefining Mechanical Load (Block)Defining the pl controller.........5-8Starting Simulation..5-12Adding a Rectangular Plot(Pl Controller)... 5-13Adjusting Plot Properties.5-14Checking the block Sequence..5-16Using Automatic Block Sorting5-16Using Manual Block Sorting5-16Rerun the Simulation(PI Controller)Simulation Results(PI Controller)5-176. Using VHDL-AMS Components forModelingVHDL-AMS Components,,,,.6-2Modify the pl controller Design.6-3Save the project with a new name6-3Delete the dc Machine component6-4Placing and Arranging the New VHDL-AMs Components on the sheet6-4Connecting the New VHDL-AMS Components 6-4Defining VHDL-AMS DC Machine values6-4Defining Connections for Machine Current..6-5Defining Simulation ParametersAnalyze and Display Simulation Results(VHDLAMS6-67. Variants of PWM ModelingPWM Modeling Overview7-2Create a New Project for the pWm models ..7-3Setting Initial ConditionsPWM Modeling Using EquationsDefining Simulation Parameters7-4Displaying Simulation Results with Reports 7-4Simulation results 7-6PWM Modeling with Equations and Time Function7-6PWM Modeling with State Graph Components 7-8Place and arrange the components on the sheet7-8Define Component properties翻国7-9PWM Modeling with Block Diagram Components 7Placing and Arranging the Components on theSheet7-118. Importing Legacy SchematicsTranslating a Legacy Schematic..8-2Importing the legacy Schematic8-2Starting an analysis...,,8-6Plotting Simulation Results8-7Estimated time tooplete this guide45 minutes

现代数字信号处理及其应用（何子述）仿真作业程序题

基于Census变换及Hamming距离的三维立体重建Matlab程序，用于从左右灰度图像得到视差图。结果经Middlebury标准测试集测试。

QQ可用 Directshow实现的虚拟摄像头（win10+vs2013,c++代码）增加图片选择

神经网络 反向传播 动量 自适应学习 课程设计 matlab 原代码 附设计文档

VCS lab 和 VCS lab guide

人脸检测作为物体检测问题的一个特例,长期以来一直备受关注,已经开始广泛应用到全新人机界面、基于内容的检索、基于目标的视频压缩、数字视频处理、视觉监测等许多领域。 本论文研究的是如何准确地在复杂背景的灰度或彩色图像中测人脸,同时验证了结合肤色等多种信息融合的方法是提高检测速度的有效途径之一。利用目前较为流行的AdaBoost算法的一个改进算法——Gentle AdaBoost算法,设计实现了以这个算法为核心的快速人脸检测系统,系统分训练和检测两部分,训练的最终目的就是得到一多层分类器结构,人脸检测的效率和检测速度在很大程度上是由这种结构形式决定的。通过一系列的比较得出样本选取、特征选取、核心算法

更深入理解模板匹配技术，能够独立根据已知算法（相关匹配（Correlation Matching）、基于Hausdorff距离匹配方法 及考虑对场景图象距离变换（Distance Transform）的Hausdorff距离匹配方法）在MATLAB下编程实现相关的模板匹配技术，并通过结果，对比不同算法的优缺点。1）利用①相关匹配（Correlation Matching）、②基于Hausdorff距离匹配方法 及③考虑对场景图象距离变换（Distance Transform）的Hausdorff距离匹配方法,实现模板目标在场景图象中的定位。2）对于每个模板分别给出最后的目标定位位置坐标（左