matlab-from-entry-to-the-master

Learning Vector Quantization (LVQ) is a supervised version of vector quantization

A New Approach to Fourier Synthesis With Application to Neural Encoding and Speech Classification

PLS程序及实例文件汇总 PLS组分选择随机测定(Purpose: randomization test for PLS component selection )

利用MATLAB实现的最小包围矩形算法，精简实用(MATLAB implementation of the minimum bounding rectangle algorithm)

多核处理多特征的融合（matlab实现——提供测试数据）(Multicore processing multi-feature fusion (matlab achieve- to provide test data))

通信系统设计，数字带通传输系统仿真Matlab代码 1. 比较BPSK与QPSK两种调制方式的误码率和误比特率性能（注意QPSK的误码率不同于误比特率），横坐标为SNR，并与理论曲线比较，分析解释仿真图。 2. 要求使用Matlab/C语言/Matlab-simulink中的任一种工具实现。 3. 代码中每个模块都要有详细注释说明。 (Communications systems design, digital bandpass transmission system simulation Matlab code 1. Comparison of BER QPSK and BPSK modulation methods and bit error rate performance (note QPSK error rate is different bit error rate), the horizontal axis is SNR, and compared with the theoretical curve, analysis and interpretation of simulation map. 2. requires the use of Matlab/C language/Matlab-simulink any one tool to achieve. 3. The code of each module must have a detailed explanatory notes.)

说明：  基于遗传算法的TSP优化Matlab源码实现(TSP optimization based on genetic algorithm MATLAB source code implementation)

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)

几种版本的支持向量机工具箱,都是能用的 很方便(Several versions of SVM toolbox, are very easy to use )

最经典的matlab介绍微粒群算法的书，不好买的。(The most classic PSO algorithm matlab introduction of the book, not bought.)