matlabxiaobofenxi

说明：  matlab经典算法程序的源代码，包括差值、拟合、绘图、解方程等。(classical algorithm matlab program' s source code, including the difference, fitting, drawing, solving equations and so on.)

ERA模态参数提取方法，根据特征参数提取(MOdal ERA method)

改进等高线拟合代码，很有价值。(improve contour fitting code and of great value.)

It is used for understanding the phenomenon of pendulum and chaos. It s good for beginners.

基于Matlab/Simulink建立的仿真模型，可以进行基于综合潮流控制器UPFC的电力系统仿真与分析。(Based on the simulation model established by Matlab/Simulink, the simulation and analysis of power system based on integrated power flow controller UPFC can be carried out. )

本程序师描述blast检测的仿真程序，描述了该码的各种性能，并对仿真结果进行了分析(The programmer describes blast testing simulation program, describes the various properties of the code, and simulation results are analyzed)

MATLAB求音频短时能量，可以快速用matlab获取音频短时能量(MATLAB and audio short-term energy, you can quickly matlab audio short-term energy)

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 )

线性最优状态调节器，一阶系统，Riccati方程的求解(Linear optimal state regulator, first-order system, Riccati equation)

滑模Matlab的实例，对于初学者相当好用，可以借鉴一下。(Sliding Matlab examples, very useful for beginners, you can learn it.)