cours-SMI4-analyse-numerique-TP

Digital Signal Processing-A Computer-Based Approach(Second Edition)Sanjit K.Mitra实验指导书练习题matlab程序(Digital Signal Processing-A Computer-Based Approach (Second Edition) Sanjit K. Mitra guide book Exercises experimental procedures matlab)

较为详细的介绍倒谱法，传统倒谱法以及对倒谱法的改进算法，以及对倒谱法进行MATLAB实验(A detailed introduction of cepstrum method, the traditional cepstrum method, and the cepstrum method of improved algorithm, and MATLAB experiments of cepstrum method)

GPS信号跟踪与捕获，相关及非相关累积算法(GPS signal tracking and capture, accumulation-related and non related algorithms)

code source compression image using Haar wavelet By Arash Fattahi, Omid Aladini {r_ash,omid}@cs.sharif.edu To compress an image use this command in MATLAB: haar_compression(FILE_NAME,COMP_LEVEL,MOSAIC_SIZE) example: haar_compression( dancer.jpg ,50,3) //Haar mosaic size will be 2^3

matlab编写的蚁群算法，能够实现基本的路径优化(ant colony algorithm matlab prepared)

本程序为粒子算法找最小值，很有启发意义，大家可以借鉴下(This program is to find the minimum particle algorithm, very instructive, we can learn from the next)

这写都是我在做-x LMS噪声除噪中的一些源代码，最后的代码也有，请大家自己看(It was all my doing-x LMS noise than noise in some of the source code, the final code also, please look at their own)

matlab for copula 最全的copula代码(matlab for copula)

matlab generation.mdl

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.)