matlabSuperTutorial

VC_与MATLAB混合编程在语音处理中的应用(VC_ mixed with the MATLAB programming in Speech Processing)

本程序是矩形波的产生。第零步定义了要产生的波形的所有特征参数，矩形波的持续时间WIDTH，矩形波的采样点数POINTS,载波频率为F0，这个频率的最终引入是便于使用RF频率发射波形。第一步包括产生矩形波，并将其调制到RF上，注意，产生的信号的持续时间是矩形波宽度的5倍，这样，总的采样点数就是5*POINTS。同时还应注意，如果要产生一个基带信号，必须设置T0=0.第二步是画出所产生矩形波的源代码。( This procedure is rectangle wave production. Step to produce stage defined the waveform of all characteristic parameters, the duration of the rectangle wave WIDTH, rectangle wave sampling POINTS POINTS, carrier frequency F0, this frequency for the ultimate introduction is easy to use RF frequency emission waveforms. The first step including generating rectangle wave, and modulated to RF, attention, produce the duration of the signal is five times the width of rectangle wave, so, overall sampling POINTS is 5* POINTS. Also, note that if you want to produce a baseband signals must set T0 = 0. The second step is to draw a rectangular wave generated by the source code. )

This a matlab code for nested dissection.(This Matlab code for a nested dissection.)

一个用matlab写的GUI图像时钟程序，还显示日期，时钟读取的是系统时间，很有趣，感兴趣的朋友可以下下来看看( matlab write GUI image clock programs, but also to display the date, the clock read is the system time, very interesting, interest friends can look down )

说明：  Matlab在图像处理与目标识别方面的应用 附有例题 1染色体识别与统计 2汽车牌照定位与字符识别 3 基于BP神经网络识别字符的简单实验(Matlab image processing and target recognition in the application of a chromosome with Example 2 License Plate Recognition and Statistical location and character recognition based on BP neural network to recognize three characters in a simple experiment)

说明：  著名的Mackey—Glass问题的源程序，你可以试着下载一下，希望对你有一些帮助！(Well-known Mackey-Glass problem of the source, you can try to download what I hope you have some help!)

实现图像的显著性，真正的原始代码，非修改，来自于外国著名实验室。(saliency map)

MATLAB help file for OSSR

刘金坤先进PID控制第二版第四章的仿真程序(Advanced PID control刘金坤Chapter IV of the second edition of the simulation program)

In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. (In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. )