QPSKMATLAB

说明：  中国标准数字地面电视中重要仿真代码 可实用化的(The practical matlab simulation code for the chinese standard DTV )

CryptAPi操作的DEMO，全部测试CryptAPI函数，其中针对之前的cSP操作方式进行相关的测试和开发，针对使用者有很好的帮助。(DEMO CryptAPi operation, all the tests CryptAPI function, which for the previous cSP operation related testing and development, there is a good help for the user.)

LDPC的分层NMS算法的matlab仿真程序，包含编码程序、译码程序以及画误码率图程序(NMS layered LDPC algorithm matlab simulation program, including coding procedures, as well as painting BER decoding process diagram program)

模糊控制器，能够实现模糊控制，自适应迷糊控制(Fuzzy Control)

用于进行MNF变换，mnf用于对高维数据进行降维，特征提取(For MNF transformation, MNF is used for dimensionality reduction and feature extraction of high-dimensional data.)

改进后的基于模糊控制理论的变电站电压无功控制方法。(Improved voltage and reactive power control method based on fuzzy control theory substation.)

WCDMA的simulink编程与开开发，相对来说比较详细，找的比较辛苦。 (WCDMA in simulink programming and open development, is relatively detailed, and looking hard.)

高光谱图像处理，ppi算法，MATLAB，可以直接使用，纯像元指数端元提取( Hyperspectral image processing, ppi algorithms, MATLAB, can be used directly as the dollar index pure endmember extraction)

STK编程手册之Connect编程，利用MATLAB、VC或者Perl等实现对STK的控制。(STK Connect programming manual programming, use of MATLAB, VC, or Perl, etc. to achieve the control of STK.)

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)