Sherif Mohamed Dec 2018

说明：  灰色预测 命令形式为x=[19519,19578,19637,19695,16602,25723,30379,34473,38485,40514,42400,48337] gm(x)(Grey command of the form x = [19519,19578,19637,19695,16602,25723,30379,34473,38485,40514,42400,48337] gm (x))

matlab因子分析的几个例程 包括：基于协方差矩阵或相关矩阵系数矩阵的因子分析 ，与基于样本观测值矩阵的因子分析(matlab factor analysis of several routines include: factor covariance matrix or correlation matrix coefficient matrix-based analysis, and factor sample observations Matrix Analysis)

空气中声传播的fdtd例程，简单可用，希望对大家有帮助(Fdtd airborne sound propagation routines, simply available, we hope to help)

基于动态规划算法的蛋白质序列比对 Needleman-Wunsch Smith-Waterman(protein sequence alignment Needleman-Wunsch Smith-Waterman)

this code contains coding of ofdm simulation. this may helpfull

It can be applyed forthe Spectral Element Method conbined finite element and spectral method to solve the 2D wave equation.as a pecial case is SH. dynamic fault with slip weakening is considered either.

基于matlab的gps仿真，包括理论原理、仿真方法、仿真结果及其分析等(Based matlab gps Simulation, including the theoretical principles of simulation methods, simulation results analysis)

A Guide to MATLAB for Beginners and Experienced Users - Hunt Lipsman & Rosenberg(A Guide to MATLAB for Beginners and Experienced Users- Hunt Lipsman & Rosenberg)

说明：  气候分析中检验突变的经典程序，如滑动t检验，cv，滑动f检验等(Climate Analysis classic mutation testing procedures, such as sliding t test, cv, sliding f inspection)

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)