v60-22

说明：  该算法连续系统的积分分离式PID算法,用MATlab开发，能够管直接运行,当控制量与设定值偏差较大时，取消积分作用，以免积分作用过大引起系统的稳定性降低。(The algorithm of the integral continuous system separate PID algorithm, developed using Matlab and can directly run the tube, when the control volume and settings deviation is larger, the abolition of integral action, so as not to cause too large integral role in the stability of the system lower.)

结构动力分析计算节点垂直方向的动力响应matlab程序(Dynamic Analysis of compute nodes vertical dynamic response matlab program)

matlab code generates egarchmodel

image mosaicing using sift

SVM(支撑向量机）分类MATLAB程序，需要安装SVM工具箱(SVM (support vector machine) classifier matlab program, you need to install SVM toolbox)

算屈服点，延性系数 采用matlab编写的 通用屈服弯矩法(matlab )

利用机器学习中的K邻近、感知机和logistic回归分类男女(Using KNN,perception and logistic to divide male or female)

Vectorized particle swarm optimization

chirp信号产生比较 If you are aware of this and would still like to have a pseudo-chirp then you can take a look at the example below. I show the difference between trying to generate the type of chirp you are after and a real chirp signal. I also plot the derivative of the resulting signals, so I can highlight that between half cycles you will have a sometimes subtle (sometimes not so subtle) jump in gradient. (chirp signal generation If you are aware of this and would still like to have a pseudo-chirp then you can take a look at the example below. I show the difference between trying to generate the type of chirp you are after and a real chirp signal. I also plot the derivative of the resulting signals, so I can highlight that between half cycles you will have a sometimes subtle (sometimes not so subtle) jump in gradient. )

：在介绍过程监控主要内容及方法的基础上，归纳分析了统计过程监控的发展，详细阐述了传统 的PCA、PCR、PLS、FDA、HMM 和几种改进的PCA方法．指出，将人的经验和专家知识融人到PCA统计过程 监控，提高PCA的故障检测、隔离能力，完善故障诊断与评价能力，将是一个有价值的研究方向(: In the introduction the main content and methods of process monitoring based on the inductive analysis of the statistical process monitoring of development, elaborated on the traditional PCA, PCR, PLS, FDA, HMM, and several improved PCA method. Pointed out that the human experience and financial expertise to the PCA statistical process monitoring of people and improve the PCA fault detection, isolation, and improve fault diagnosis and evaluation capacity, will be a valuable research)