lempel_ziv

改程序在噪声幅度与信号幅度相当的情况下，运用MSL算法能够实现原信号的优良输出。(Magnitude of change procedures and the amplitude of the signal in the noise equivalent circumstances, the use of the original signal MSL algorithm can achieve good output.)

Assistive technology for people made code in matlab

hystersis control algorith which is bein done in matlab

有关matlab的图像处理课件，供初学者学习参考。(Matlab image processing related courseware for beginners to learn information.)

Brain MR Image segmentation using k-means clustering

compute the background image

用matlab编写的三维魔方模拟显示，直接运行first.m即可(Three-dimensional cube simulation using matlab display, can be run directly first.m)

基于SVR的线性系统内部模型辨识建模及校验的仿真程序， 由于辨识信号采用的都是随机信号，不是数值固定的信号，所以程序每次运行的结果都可能有所不同。(Based the SVR system of linear internal model identification modeling and verification simulation program identification signal are random signal, not the value of the fixed signal, so the program each time you run the results are likely to differ.)

用matlab 软件进行图像处理，对比度、灰度处理。(Matlab image processing procedure, but the image contrast, gray processing. )

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.