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研一，学校开了数值分析这门课，而且要求用matlab进行上机试验，就写数值分析常微分方程的7个MATLAB算法，都是能够套用的M文件。还有我自己的上机作业。很不错的，能参考。要想要其它章的算法，我都已经上传了。(Kenichi, the school opened the numerical analysis of the course, but also carried out on machines with matlab test, on the numerical analysis of ordinary differential equations to write the seven MATLAB algorithms, are able to apply the M-file. Also on my own machine operation. Very good, can draw on. To want the algorithm to other chapters, I have already uploaded.)

matlab7图书里面的所有matlab代码，对初学者很有用，可以用来来纳西基本操作，熟悉基本的子程序，或供工程人员进行功能仿真是很的参考(Book inside matlab7 all matlab code, very useful for beginners and can be used to Naxi basic operation, familiar with the basic subroutine, or by project team members to conduct functional simulation is the reference)

说明：  MATLAB-数据处理-一个文件数据处理小程序(MATLAB-data processing-a small data-processing document procedures)

使用Matlab编程工具对单纯形法的基本算法的实现，不包括二阶段修正部分(Simplex algorithm)

Round Numeric array element values to IEC 60063 (E-Series) component values.

MATLAB中几种功率谱估计函数的比较分析与选择(MATLAB power spectrum estimation function of several comparative analysis and selection)

说明：  使用matlab实现信息瓶颈中的aIB算法源程序(Matlab implementation using information bottleneck algorithm source code in aIB)

programme matlab 1D pml

对信号进行小波分解，用硬阈值方法去除噪声，进而提高精度(right signal wavelet decomposition, with a hard threshold to remove noise, and to improve accuracy)

Otsu-最大类间方差Matlab代码 最大类间方差法原理：最大类间方差法是由日本学者大津于1979年提出的,是一种自适应的阈值确定的方法,又叫大津法,简称OTSU。它是按图像的灰度特性,将图像分成背景和目标2 部分。背景和目标之间的类间方差 ％ 大,说明构成图像的2 部分的差别越大,当部分目标错分为背景或部分背景错分为目标都会导致2 部 ％ 分差别变小。(Otsu- Otsu Matlab code Otsu Principle : Otsu law by Japanese scholars in the large-1979's, is an adaptive threshold established methodology, also known as big-law, referred to Otsu. It is based on image characteristics of the gray image can be divided into the background and objectives of Part 2. Background and objectives between the between-class variance%, which meant that the two images form part of the greater difference, When some background into the wrong target or part of the background into the wrong target will lead to sub-2% difference becomes smaller.)