dct+ss

被控对象为两惯性模型，调节器为PI调节器并在系统中加入了整数阶干扰观测器(Inertial model for the two charged objects, regulator for the PI regulator and in the system by adding the integer-order disturbance observer)

用CHM格式罗列了常用的MATLAB函数，便于在一时无法想起时，迅速查找函数(CHM format with a list of commonly used MATLAB functions, easy to remember the moment when you can not quickly find the function)

说明：  机器人躲避障碍仿真设计程序,来源于因特网.非本人设计(robot avoid obstacles simulation design process, and from the Internet. I-Design)

傅里叶变换与逆变换, Matlab程序。The main focus of this lab lab is converting between the frequency and time domain. (Fourier Transform Forward and inverse)

任务： 1） 借助MATLAB画出误差性能曲面和误差性能曲面的等值曲线（参考PPT2.1第17页的两幅图）； 2） 写出最陡下降法以及LMS算法的计算公式（取 ）； 3） 用MATLAB产生方差为0.05, 均值为0白噪音S(n)，并画出某次采样得到的波形（即产生任意一个噪声随机序列）； 4） 根据 2）中的公式，并利用 3）中产生的S(n)，在 1）中的误差性能曲面的等值曲线上叠加画出采用最陡下降法以及LMS法时H(n)的在叠代过程中的轨迹曲线（参考PPT2.1第17页的右下图的曲线1和曲线2）。 5）用MATLAB计算并画出LMS法时 随时间n的变化曲线（对应S(n)的某一次的一次实现）和e(n)波形； 注意：某一次实现的结果并不能从统计的角度反映实验的结果 的正确性，为得到具有统计特性的实验结果，可用足够多次的 实验结果的平均值作为实验的结果。用MATLAB计算并画出 采用LMS法时，J(n)的100次实验结果的平均值随时间n的变 化曲线（即 生成随机噪声信号并计算结果，重复执行100次， 求平均结果）。 6）在 1）中的误差性能曲面的等值曲线上，叠加画出采用LMS法得到的100次实验中的H(n)的平均值的轨迹曲线； (Task: 1 ) Draw with MATLAB error performance surface and surface contour error performance curve ( refer PPT2.1 two chart on page 17 ) 2 ) Write the steepest descent method and the LMS algorithm formula ( take ) 3 ) Using MATLAB to generate variance of 0.05 with a mean of 0 white noise S (n), and draw a particular sampling waveform ( ie, any noise generated random sequence ) 4 ) based on 2 ) of the formula , and use 3 ) generated in S (n), in a ) the error performance curves superimposed on the surface contour plot using the steepest descent method and the LMS method when H (n) the iterative process in the trajectory curve ( refer PPT2.1 page 17 bottom right of the curves 1 and 2 ) . 5 ) using MATLAB LMS method is used calculate and draw the curve with time n (corresponding to S (n) of a first implementation of a ) and e (n) waveform Note : in a first implementation of the results are not reflected from a statistical point of view of accuracy of the experimental results ,)

dea in matlab for windows

Edge detection in microscopy images using curvelets

车牌识别系统,在Matlab下运行。。。。(che pai shi bie)

cellular-d2d-caching

matlab 6.5电子书，包含了一整本书的内容，内容清晰易懂，查看很方便。对于高版本的matlab环境也适用(Matlab 6.5 e-book contains an entire book, clear and easy to understand, the view is very convenient. Also applies for the high version of the Matlab environment)