MatlabPlot

局部放电的n-q-phi和dltU处理程序，还有其他的一些有用的程序(Partial discharge of the nq-phi and dltU process, there are some other useful programs)

it is very useful paper for multilevel converter

Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification. This document explains the use of libsvm.

Volumetric plot of a partially translucent 3D-Matrix (3-Tensor) in Matlab.

this is a kinect mouse control sample. just run it or you could copy and paste on your programe(Mouse control demo)

以优化SVM算法的参数c和g为例，对CS算法MATLAB源码进行了逐行中文注解。(SVM algorithm to optimize the parameters c and g, for example, the CS algorithm MATLAB source was progressive Chinese annotations.)

了解随机信号自身的特性，包括均值（数学期望）、方差、相关函数、频谱及功率谱密度等。(Understanding of random signal their characteristics, including mean (mathematical expectation), variance, correlation function, spectrum and power spectral density.)

EKF UKF 滤波算法在MATLAB仿真软件中的仿真，并进行对比(EKF UKF filtering algorithm in MATLAB software simulation, and compared)

这是模式识别中最小错误率Bayes分类器设计方案。 自行完善了在不同先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。 全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。 调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。 调用最小错误率贝叶斯分类器决策子函数时，根据先验概率数组，通过比较概率大小判断一个体重身高二维向量代表的人是男是女。 主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小错误率贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到不同先验概率条件下错误率的统计。 (This is the minimum error rate pattern recognition Bayes classifier design. Self- improvement prior probability in different conditions , male , female and total error rate error rate statistics , into which each array . All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions . Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector third step is to application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function . Call the minimum error rate decision Functions Bayesian)

图像特征提取的总结，用MATLAB模糊聚类算法进行图像分割，阀值分割及特征提取的资料和作业。(Summary of the image feature extraction, fuzzy clustering algorithm using MATLAB for image segmentation, threshold segmentation and feature extraction of data and operations.)