Vector_Control_SVPWM

模糊控制MDL模糊MATLABfuzzypid(MDL fuzzy control fuzzy MATLAB uzzypid)

自适应画线，可用Matlab编程,也可用Mathematica软件编程(Adaptive draw lines available Matlab programming)

与ART算法相对应，采用乘法迭代算法MART进行层析成像反演的必备程序。(And ART algorithm corresponds iterative algorithm using multiplication MART tomography inversion essential procedures.)

说明：  复杂网络BA模型matlab代码，返回网络图的邻接矩阵，代码中采用稀疏矩阵，极大地释放内存，提高效率。(BA model complex network matlab code, return to the network adjacency matrix, the code used in sparse matrix, which greatly release memory and improve efficiency.)

量子遗传算法MATLAB源代码，内含多个子文件，测试时运行main文件即可(Quantum genetic algorithm MATLAB source code that contains multiple sub documents, test documents can be run main)

三节点平面应力单元有限元分析，计算出了其节点力、位移和应力。(Three-node plane stress element finite element analysis to calculate the strength of its nodes, displacement and stress.)

“RADAR SIGNAL ANALYSIS AND PROCESSING USING MATLAB”。matlab对雷达信号的分析与处理（英文版），是学习处理雷达信号的入门教材。主要内容有雷达系统原理介绍和常用matlab函数。(" RADAR SIGNAL ANALYSIS AND PROCESSING USING MATLAB" . is a primary book of radar signal processing. The main contents is introduction of radar systems and some matlab functions.)

Gardner算法的Matlab仿真与实现(simulation and implementation of Gardner algorithm)

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)

文化算法的MATLAB实现。实验结果表明该算法具有良好的性能。(MATLAB implementation of cultural algorithms. Experimental results show that the algorithm has good performance.)