MOM

用于处理信号，对信号进行小波包分解，此处进行了三层分解计算，可以进行迭代。(Used to process the signal, the wavelet packet decomposition of the signal, where the three-tier decomposition of the calculation can be iterated.)

说明：  数字信号处理DSP中，DFT离散傅里叶变换等上机作业。(In digital signal processing DSP, DFT discrete Fourier transform.)

说明：  在学习数字信号处理算法程序中用VC编写的几个通用算法程序。 卷积计算/DFT与FFT实现/(In the learning process of digital signal processing algorithms using VC General Algorithm for the preparation of several procedures. Convolution calculation/DFT and FFT realization /)

非常实用的时域仿真法暂态分析工具，利用牛顿法求解系统的微分方程组和代数方程组，得到转子摇摆曲线，判断暂态是否稳定(Very useful time-domain simulation tool for transient analysis method, using Newton method for solving systems of differential equations and algebraic equations, the rotor swing curves, to determine the stability of transient)

book on markov models and techniques

针对随机结构随机激励下的动力响应概率分布求解，基于广义概率密度方法(the calculation of the generalized probability density function)

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))

网上看到很多关于矩阵求逆运算的代码，都很杂很乱，我把代码重新真理了一边，可以直接编译运行(See a lot of online matrix inversion code, very complex mess, I put the code back to the side of truth, you can directly compile and run)

用python写的牛顿迭代法和牛顿插值法，数值分析的实验(Newton iteration method and Newton interpolation method written in Python, numerical analysis experiment.)

关于流体计算软件FLUENT中Y+设置的一些建设性的讨论，值得大家参考。(On computational fluid dynamics software FLUENT some constructive discussions in the Y+ set is worth your consideration.)