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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))

电容层析成像的ART算法演示实例,并带有详细的说明(An Example of ART Algorithm for Electrical Capacitance Tomography)

python编写SM3密码杂凑算法,测试字符串abc, abcd*16(written in python SM3 password hash algorithm, the test string abc, abcd.* 16)

三角形网格上的线性有限元方法求解Helmholtz问题，多项式重构以及Richardson外推(solve the Helmholtz equation with robin boundary condition on triangulation mesh, PPR and Richardson extrapolation)

frotran输入矩阵自编小程序，可以生成任意大小矩阵，并写入制定文件(frotran input matrix composing small program that can generate any size matrix, developed and written documents)

说明：  矩阵求逆，使用fortran语言编写，希望能对有需要的朋友有所帮助(Matrix inversion, written in FORTRAN language, hoping to help friends in need)

毕业设计有用，相控阵天线的方向图（切比雪夫加权），基于matlab GUI界面设计。( Graduation useful Phased array antenna pattern (Chebyshev weights), Based on matlab GUI interface design.)

计算偏心圆导热计算以及同位网格上的SIMPLE算法 (Calculating thermal calculations and eccentric position on the grid with SIMPLE algorithm)

是用MATLABA编写的遗传运算发的一个小程序 挺好用的 大家(MATLABA is prepared by the genetic operator issued a small procedure very well, we try to use)

利用Python实现特征的MinMax标准化和Z-Score标准化两种特征归一化方法。并用原特征、两种归一化特征分别进行朴素贝叶斯模型训练，比较模型性能。(Two normalization methods of MinMax normalization and Z-Score standardization are implemented by Python. The naive Bayes model is trained with the original features and two normalization features respectively to compare the performance of the model.)