psk-fsk

This program is used to explain how PCA works and the idea behind the method. This example is given in the ISA book (Chapter 8, simple example) The process is composed of a valve a thermometer and a fermenter. The valve is used to control the flow rate of cooling water. The thermometer is used to measure the temperature of the fermenter.

应用matlab开发的ofdm源代码，其中和QAM调制方式做了比较，内含部分说明文档(Application development of OFDM matlab source code and QAM modulation which has done a comparison, contains some documentation)

用MATLAB写的，关于数据挖掘的很多算法，如PCA,K-MEANS等，最重要的他是图形化界面(Written using MATLAB on a lot of data mining algorithms, such as PCA, K-MEANS, etc., the most important he is a graphical interface)

deltal调制的simulink模型，希望对大家有用(simulink module of deltal modulation，hope it can be helpful)

数据快照的特征提取，获得基模态、特征值和模态系数，以及数据的后处理。(Feature extraction of data snapshot, obtaining basic modes, eigenvalues and modal coefficients, and post-processing of data.)

windmill driven by PMSG and rectifier

求积分的matlab源程序,该程序的执行效率比较高，并且简单。(Quadrature matlab source, the efficiency of the program is relatively high, and simple.)

介绍了并联机器人的导航算法，实用起来方便，实现了仿真的功能(Introduced parallel robot navigation algorithm, practical it easy to achieve a simulation function)

它是Mann-Kendall（非参数检验）突变检测算法的MATLAB源码。给出了单边Mann-Kendall突变检测算法和双边Mann-Kendall突变检测算法的matlab的详细程序。适合做有突变点的非参数检验和matlab爱好者使用。(It is the Mann-Kendall (nonparametric test) mutation detection algorithm MATLAB source. A detailed program of unilateral Mann-Kendall mutation detection algorithm and bilateral Mann-Kendall mutation detection algorithm matlab s. Suitable for point mutations and non-parametric tests matlab enthusiasts.)

GMDH_main为GMDH主函数； variable_Combin为输入层初始变量选为x1,x1^2,x1*x2,x2^2,x2时的输入变量矩阵值 variable_select计算X_train训练输入数据,Y_train训练输出数据,X_test测试输入数据,Y_test测试输出数据 Combin为求变量的两两组合 Sym_Combin为求符号变量的两两组合 PE_AIC求每层各神经元的参数估计W，及训练数据在参数估计后估计的输出out_train，测试数据在参数估计后的估计输出out_test，还有与实际比较的误差平方和PESS， 以及准则值AIC sym_representation求最终的输入输出符号表达式 Criterion_value求准则值 (GMDH_main main function for the GMDH variable_Combin initial variables chosen for the input layer, x1, x1 ^ 2, x1* x2, x2 ^ 2, x2 the value of the input variable matrix calculation X_train variable_select training input data, Y_train training output data, X_test test input data, Y_test for the sake of the test output data Combin pairwise combination of variables for the sake of symbolic variables Sym_Combin pairwise combinations PE_AIC neurons find each parameter estimation of the W, and after the training data is estimated in the estimation of output out_train, test data After the parameter estimates of the output estimated out_test, also compared with the actual sum of squared errors PESS, as well as the final criterion value AIC sym_representation seek the input and output values ​ ​ of symbolic expressions Criterion_value find criteria)