signalandsystemwithmatlab

MATLAB FILE USED FOR CODING FOR MPC AND PID CONTROLLER IN A GIVEN PROCESS

这是龚纯编著的《matlab语言常用算法程序集》的PDF版。上篇是基础，下篇是大量的程序算法。(This is pure Gong compiled the " matlab common algorithms assembly language" of the PDF version. The first part is the basis Xiapian is a lot of program algorithm.)

深入简出的分析了MATLAB符号运算和绘图功能,并附有大量实例,便于自学(Chien-depth analysis of the MATLAB Symbolic computing and graphics, together with a large number of examples, easy to self-)

基于三电平空间电压质量控制的异步电动机直接转矩控制(Based on a three-level quality control of space voltage induction motor direct torque control)

数值分析计算程序例子，三次样条插值法，边界条件：端点导数值已知。(Numerical the analysis calculation procedures example, cubic spline interpolation, boundary conditions: endpoint derivative)

Start with the runlocalization track.m which is the entrance function to your lab. This function reads two les determined by simoutle and maple input arguments which contain information about sensor readings and the map of the environment respectively, runs a loop for all the sensor readings and calls the ekf localize.m to perform one iteration of EKF localization on the readings and plots the estimation(red)/ground truth(green) and odometry(blue) information.(This lab consists of two parts: 1. A preparatory case study with a standard Kalman lter where you learn more about the behavior of the Kalman lter. Very little extra code is needed. 2. The main lab 1 problem in which you need to complete an implementation of an Extended Kalman lter based robot localization.)

set up the trellis with code generator G in binary matrix form.

说明：  模糊控制PID的simulink仿真(Simulink simulation of fuzzy PID control)

蓝牙中的跳频实现模型,利用matlab中的simulink(Bluetooth s frequency hopping to achieve model simulink in matlab)

为实现合成孔径雷达（SAR）图像分类算法的测试与评估，将VC/Matlab 混合编程技术应用到SAR 图像分类平台开发中，分析与 比较了4 种VC/Matlab 混合编程方法及各自优缺点，并着重研究了基于组件对象模型（COM）的VC/Matlab 混合编程方法。使用Matlab COM 编译器创建了SAR 图像分类算法组件，在VC 中调用其导出的接口函数。在此基础上，完成了SAR 图像分类平台的实例开发且 可脱离Matlab 环境运行。实验结果表明，该方法较好地发挥了VC 与Matlab 各自的优势，提高了SAR 图像分类平台开发的效率。(In order to test synthetic aperture radar （SAR） image classification algorithm，VC/Matlab mixed programming technology was used in SAR image classification platform development. Four VC/Matlab mixed programming methods were introduced and analyzed. Comparing with other three methods，the method based on component object model （COM） was studied particularly. SAR image classification algorithm component was created by Matlab COM complier，and its interface function could be invocated with VC. Using this method，a SAR image classification platform was realized. The platform could run without Matlab. The experimental result shows a good combination of VC and Matlab. So，developing efficiency could be enhanced a lot.)