MSKmod

用MATLAB编写的小波模极大值一维去噪程序，程序完整。(Prepared using MATLAB one-dimensional wavelet modulus maxima denoising process, the program integrity.)

顺序聚类算法的改进-MBSAS，并在MATLAB上实现该算法。(Clustering algorithm in order to improve-MBSAS, and the algorithm in MATLAB to achieve.)

Pattern Recognision with matlab(Pattern Recognision)

Thi is a Binary BAT algorithm

测试对于整个测试集的识别率对于测试集合的识别率(Test for the entire test set recognition rate)

a matlab toolbox for multidimension scaling and clustering of a 2 dimensional or 3 dimensional data matrix..

精通MATLAB图像处理源码 大家尽情下吧(Proficient in MATLAB image processing source code)

数字预失真Wiener模型的matlab实现(Digital predistortion Wiener model matlab implementation)

It will make negative of input image

This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. Before getting to a description of PCA, this tutorial first introduces mathematical concepts that will be used in PCA. It covers standard deviation, covariance, eigenvectors and eigenvalues. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.