SPeech_1_1

国外高校的关于图像区域生长的算法源码，编写的代码非常紧凑，算法执行效率高(Image region growing algorithm by abroad univertity and the algrorithm level is very high and efficient)

fuzzy controll system introduction

分型计算李雅普诺夫指数的一个程序，可以参考(Typing a program Lyapunov exponent calculation, reference)

基于短时傅里叶变换的非平稳信号的时频分析(Based on Short time fourier transform,signal s time-frequecy analysis.)

SVM工具箱，包括完整的工具箱，演示程序和说明文档(SVM toolbox, including a complete kit, demo program and documentation)

项目中所做的ADC的matlab源代码，相信会有用(original matlab source code for ADC from the item i was doing，hoping to be helpful)

programme permet de calculer la racine primitive

说明：  用于图像拼接，图像序列的柱面全景拼接算法，matlab仿真程序(For image mosaic, image sequence cylindrical panorama stitching algorithm, matlab simulation program)

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.

feature extraction with matlab