mouse-tracking

大气层内航天器飞行动力学matlab仿真模型(The atmosphere inside the spacecraft flight dynamics matlab simulation model)

gold.m is mfile that generate gold sequency.

Image Segmentation & Extraction

这是基于MATLAB环境的fisher分类判别的源代码，适合于统计专业人士参考(This is the fisher-based MATLAB environment, classification and discrimination of the source code, suitable for professional reference statistics)

可以从一幅含有头和肩部的图像中检测出人脸，并用矩形框框起来，将矩形框中的人脸裁剪出来并另存为80*80的图片(Can be detected an image containing a head and shoulders of a person' s face, and the frame up with a rectangle, the human face of the rectangular box to cut out and save it as 80* 80 pictures)

Processing EKG via Pan-and-Tompkins algorithm

最优波束形成的方法（包括谱加权，阵列多项式和z变换、波束空间的方向采样、最大最小设计等）(optimun array processing )

这四个程序分别为高斯消去法、列主元消去法、全主元消去法解线性方程组和Gauss-Jordan消元法求矩阵的逆。 　　程序采用MATLAB语言开发，并在MATLAB6.5下测试通过。(The four procedures were Gaussian elimination, elimination method out PCA, PCA-wide elimination method solution of linear equations and Gauss-Jordan elimination method of inverse matrix. Procedures for the use of MATLAB language development, and under MATLAB6.5 test.)

matlab 关于association rule 的自己写的函数，有3个文件, association.m：h = association(m, i, j) i=>j, m是数据，h是support和confidence，该函数只适用于单个数据 ass_item: h=ass_itset(m, a, b) 同上，但是可用于多个数据（m为数组） assrule: h = assrule(m, threshold1, threshold2) 该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence (matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix) assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)

说明：  本程序是基于马尔可夫链蒙特卡尔理论的贝叶斯工具。版本为MCMC Methods for MLP and GP and Stuff (for Matlab) V2.1 (A collection of matlab functions for Bayesian inference with Markov chain Monte Carlo (MCMC) methods. The purpose of this toolbox was to port some of the features in fbm to matlab for easier development for matlab users. )