ExtractMovieFrames

Level Set Evolution Without Re-initialization一文的matlab实现(Level Set Evolution Without Re-initialization of the matlab realize one text)

内部资料，很经典的MIMO和OFDM的课本程序，以供大家参考(it is important MIMO-OFDM program)

静态电压稳定临界点的使用求解方法，基于主导节点法的分岔类型检验法(Static voltage stability critical point of use solving method, based on the dominant node bifurcation type-test method)

最小均方误差自适应时延估计 原理 应用 改进 有很大的应用价值(LMSTDE Adaptive delay estimation theory applied to improve the application of great value)

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信号包络提取代码。可以方便地获取信号包络曲线。应用效果较好！(envelope matlab code)

这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下，自行完善了在一定先验概率的条件下，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。 调用最小风险贝叶斯分类器决策子函数时，根据先验概率，再根据自行给出的5*5的决策表，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，放入决策数组中。 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”，调用最小风险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，就可以得到在一定先验概率条件下，决策表中不同决策的错误率的统计。 (This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability 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 The third step is the 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 . Bayesian classifier )

采用PR控制策略的光伏发电并网的simulink仿真图(Simulink simulation of grid connected photovoltaic generation using PR control strategy)

人工免疫网络,实现分类,聚类,函数寻优等功能,采用matlab编写.(artificial immune network, classification, clustering, search function Excellence function, prepared using Matlab.)

动态矩阵控制算法与PID算法结合,有很强的理论性,是毕业设计的好程序(Dynamic Matrix Control algorithm combined with the PID algorithm, is very theoretical, is a graduate design program)