MPPT_OK

A Comparative Study for Orthogonal Subspace Projection and Constrained Energy Minimization

说明：  利用耦合模理论，仿真折射率调制对长周期光纤光栅的透射谱的影响，画出其透射谱线图。(Using the coupled mode theory, simulation refractive index modulation for long-period fiber grating transmission spectra of the impact of transmission lines to draw the map)

本人编写的QC-LDPC码的完整实现，采用阵列校验矩阵，极其简单，适合入门(A easy-to-learn source code of QC-LDPC encoder)

It creates an m-file for a matlab function and populate with a header template describing the purpose of the function, the input and output parameters, and other relevant information. In addition, it inserts information related to the author of the file: username, display name, computer name, windows version, and the time stamp. The command to create a MATLAB function: new myfun It is also possible to append function code at the function m-file creation time as follows: new myfun disp( Hello World! )

严格按照BP网络计算公式来设计的一个matlab程序,对BP网络进行了优化设计 优化1：设计了yyy，即在o(k)计算公式时，当网络进入平坦区时(<0.0001)学习率加大，出来后学习率又还原 优化2：v(i,j)=v(i,j)+deltv(i,j)+a*dv(i,j) (BP network in strict accordance with the formula to design a matlab program, the optimized BP network design optimization 1: Design of the yyy, that is, o (k) formula, when the network into the flat areas (< 0.0001) increase learning rate large, after the optimization of learning rate reduction 2: v (i, j) = v (i, j)+ deltv (i, j)+ a* dv (i, j) )

置乱水印，用于数字水印加入前的处理，隐藏信息(Scrambling watermark, adding watermark for digital pre-processing, hidden information)

该程序是基于matlab开发环境下的二维人脸识别代码(The program is based on matlab development environment of 2 d face recognition code )

APF谐波检测DQOABC变换，可以直接使用(APF harmonic detection DQOABC transform can be used directly)

对一维信号序列进行，短时能量法和功率谱分析，并显示波形(right one-dimensional signal sequence, and short-term energy and power spectral analysis, and display waveforms)

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)