examples

MASK（2，4，8）信号的星座图调制程序(MASK signal modulation constellation)

介绍了一种用Matlab 信号处理工具箱进行数字滤波器设计的方法。给出了工具箱中的FDATool 图形用户接 口的详细使用方法,用FDATool 进行滤波器设计,可以随时对比设计要求和滤波器特性调整参数,直观简便,在每次改变参 数时,由于计算机的超强运算能力,只需点击设计按钮,新的滤波器立即产生,避免了传统滤波器设计的大量手工运算。并 用他设计出了满足性能要求的低通数字滤波器,实现了对加速度传感器干扰振动信号的滤除,解决了工程实际问题。(This thesis int roduces a digital filter designing method using signal processing toolbox in Matlab sof tware. It gives detailedly using specifications of FDATool graphical user interface ,when designing filter using FDATool ,you can com2 pare filter designing demand with filter character so as to adjust the parameter at any moment . For powerful operation function of the computer ,when the parameters are changed ,you only need point the design button ,new filter will be produced. In this way ,a mass of manual operation will be avoided. A good lowpass digital filter is designed using FDATool ,the filter can filter preferably the acceleration sensor vibration signal and resolve the engineering problem.)

Adaptive post-processing algorithm for video signals

说明：  关于码matlab的介绍，对于初学者来说能够很快了解matlab。(On the introduction of matlab code, for beginners to quickly understand the matlab.)

这是周建兴编写的《matlab从入门到精通》第三章的所有源代码，都可以运行的出来，和课本上的一样，(This is Zhoujian Xing written 《matlab从入门到精通》第4章的所有源代码，都可以运行的出来，和课本上的一样，)

PCA及其改进算法MPCA进行人脸识别MATLAB源程序(PCA&&MPCA face recognition MATLAB code)

getting localization error by matlab

说明：  在二维平面内生成随机点并构造二维Voronoi图(Construction of 2D Voronoi diagram with random points)

system identification matlab codes...

1. 按照式计算相似性矩阵 2. 排除自身的相似度 3. 按照式计算归一化矩阵 4. 按照式计算归一化拉普拉斯图矩阵L 5. 计算L的特征向量，将前个特征值最大的向量按列放置成一个矩阵，即依次为前个特征值最大的特征向量 6. 归一化X形成矩阵Y 7. 对矩阵Y按每行为一个数据点，进行k-means聚类，第行所属的类就是原来所属的类。(1. similarity matrix based on formula computation 2. rule out your own similarity. 3. normalized matrix based on formula computation 4. normalized formula Laplasse matrix L according to formula. 5. Calculate the eigenvectors of L. Place the vectors with the largest eigenvalues in columns into a matrix, that is, the eigenvectors with the largest eigenvalues in turn. 6. normalized X formation matrix Y 7. K-means clustering is applied to matrix Y according to one data point per behavior. The first row belongs to the original class.)