Utilisation_de_Matlab_pour_l_etude_des_asservisse

采用巴特沃斯函数，构造低通滤波器，实现信号的低通滤波(lowpass filter)

此模块，是SVPWM仿真，山区判断，时间计算，PWM的产生各个部分组成。结果理想，可用于PMSM和PMLSM的控制中。(This module is SVPWM simulation, the sector judge, time calculations, the composition of each part of the PWM generation. Ideal results can be used for the control of PMSM and PMLSM.)

doa估计算法，MATLAB实现，比较简洁，可以参考一下(doa estimation algorithm, MATLAB implementation, more concise, you can refer to)

说明：  异步电动机SVPWM的matlab仿真 simulink仿真(Matlab simulation and Simulink simulation of asynchronous motor SVPWM)

用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。(Use Parzen Windows method or the kn neighbor method estimated probability density function, draw the bayes classifier, to test sample to test, and the parameter estimation is based on the classifier and get the difference of classification performance. 2. At the same time the height and weight data as the characteristic, with Fisher identification method for linear classifier, and the application of the classifier to training and test sample, investigation and test training error condition. Will the training sample and utility of decision on the drawing boundary paint, and at the same time before the Bayes method with optimal classifier also paint chart, the result of the comparison of the similarities and differences. 3. Select the above or before any a kind of method of experiment, with a method for training set in the estimation error rates, and on the test set get error rates are compared.)

用于列主元高斯消元法求解线性方程组的matlab程序(Matlab procedure for the column PCA Gauss elimination method)

是MATLAB 线性方程组的数值解法.... Gauss消去法.. 顺序Gauss消去法.. Gauss-Jordan消去法... 追赶法... 1 LU分解... Cholesky分解.....Jacobi迭代法..Gauss-Seidel迭代法.. 逐次超松弛迭代法... 梯度法.. 奇异值分解法... rref函数... lu函数... chol函数. mrdivide函数(MATLAB Efficient Programming Skills and Applications 25 Cases Analysis of Example Code Compression Section5)

采用PSO算法优化PID参数，通过调用simulink和PSO使得ITAE标准最小化(PID parameter optimization using PSO algorithm)

主要包括余弦坡度窗、帕曾窗、指数窗和高斯窗，窗函数的选择对于结果起着重要的作用，针对不同信号和不同的处理目的来确定窗函数的选择才能取得良好的效果。(It mainly includes cosine slope window, parzen window, exponential window and gauss window)

FIR低通滤波器设计,表达得还比较详细，可以借鉴参考(FIR low-pass filter design, is also expressed in more detail, you can learn from the reference)