newTon.m

基于SVM的数据分类，通过IRIS数据进行验证，效果分类准确(SVM-based data classification, through the IRIS data validation, classification accuracy results)

x-y图解法求二元精馏塔理论塔板数 本文件是一个m文件,要在matlab环境下运行(x-y graphical method for binary distillation theoretical plate number of this document is a document m, the operating environment Matlab)

说明：  MATLAB使用欧拉Euler法求解微分方程组 源程序代码(SOURCE PROGRAM CODE OF DIFFERENTIAL EQUATIONS SOURCE SOLUTION USING EULER METHOD IN MATLAB)

已知日期，计算出星期几的程序.以过测试。计算正确。请放心使用。(Caculate Weekday)

说明：  vumat案例,可以参考这个vumat子程序自行学习vumat的编写(hi. it is a file for VUMAT. it may help you to learn about it.)

cluster in quest聚类算法是基于密度和网格的聚类算法。对于大型数据库的高维数据聚类集合。(cluster in quest clustering algorithm is based on the density of the grid and clustering algorithm. For large database of high-dimensional data clustering pool.)

说明：  海浪模拟，基于PM谱，根据海浪频率波高等因素(Wave simulation, based on PM spectrum, according to wave frequency wave higher factor)

Matlab codes for Robust PCA multivariate control chart(Robust PCA multivariate control chart mainly consists two steps: Step1 Calculates the robust mean and the robust covariance of original dataset using the minimum covariance determinant (MCD). In MCD technique, finding a subset containing half of the data such that its covariance matrix has the lowest determinant, then using this subset to calculate the robust mean and the robust covariance matrix (Hubert, Rousseeuw, & Branden, 2005) Step2 Standardize data using robust mean and robust standard deviation from Step1. Apply PCA analysis, calculate the principalcomponent score matrix Y=ZA, where Z is the robust standardized data matrix, and A is p*p matrix of eigenvectors (also called principalcomponents))

说明：  FFT正变换和逆变换，了解FFT变换的实质(FFT transform and inverse transform is to understand the substance of FFT transform)

贤哥的矩阵分析与应用习题解答，答案在手，前途永久。(Shane matrix analysis and application, the answer is in hand, the future permanent.)