TSPga

数字图像处理中的有关线性变换，如角度变换等(Digital image processing of the relevant linear transformation, such as the perspective of transformation)

说明：  主元分析法的相关算法，实现主元提取，输入相关 数据即可(PCA analysis of relevant algorithms, to achieve PCA extraction, input the relevant data can be)

3.7 寸屏幕 控制电力板 大家可以学习学西 包准能用的(3.7-inch screen control panels you can learn to learn West'll usable)

主要介绍一些基于matlab开发环境的一些实用的函数程序事例，非常有用(Introduces some of the functions of some practical examples matlab program development environment based on useful)

用小波把语音分为清浊两个音，要自己改语音文件地址，会产生两个文件，效果一般(Wavelet Qingzhuo the voice is divided into two sound files to their own voice to address, will produce two documents, the effect of general)

demodulation bpsk, qpsk, 16qam, 64 qam

This code deals with data at any z-level specified by zlevel1 and uses the output generated from make_zeta_u.c, make_zeta_v.c and make_zeta_T.c file i.e. it uses the files ufile??zlevel.dat, vfile??zlevel.dat and Tfile??zlevel.dat. The output includes qiver or velocity vector plots in that particular z-level. Dependencies include quivers.m file

用matlab实现16-QAM调制与解调，在simulink里面实现，能观察16QAM信号，星座映射图，毕业设计很好的参考资料。(Using matlab to achieve 16-QAM modulation and demodulation, which in simulink realization can be observed 16QAM signal constellation map, a good reference for graduation. )

沙发大神啥都分数艾弗森沙发爱上艾弗森沙发沙发沙发(dsgsdgsdgr rg g wegsdgsgrw wer werew we)

说明：  （1）应用9×9的窗口对上述图象进行随机抽样，共抽样200块子图象； （2）将所有子图象按列相接变成一个81维的行向量； （3）对所有200个行向量进行KL变换，求出其对应的协方差矩阵的特征向量和特征值，按降序排列特征值以及所对应的特征向量； （4）选择前40个最大特征值所对应的特征向量作为主元，将原图象块向这40个特征向量上投影，所获得的投影系数就是这个子块的特征向量。 （5）求出所有子块的特征向量。 ((1) the application of 9 × 9 window of these images at random, a total sample of 200 sub-image (2) all sub-images according to out-phase into a 81-dimensional row vector (3) all 200 lines for KL transform vector, derived its corresponding covariance matrix of eigenvectors and eigenvalues, in descending order by eigenvalue and the corresponding eigenvector (4) a choice to 40 corresponding to the largest eigenvalue eigenvector as the PCA, the original image block to the 40 feature vectors on the projection, the projection coefficients obtained by this sub-block eigenvector. (5) calculated for all sub-block eigenvector.)