SAX_2006_ver

有关OFDM的资料，对需要的朋友有帮助，谢谢(about OFDM)

主动外表模型与主动形状模型，MATLAB平台下使用，内含DEMO(active appearance model)

经典的图像修复程序，matlab语言描写(The classic image fix, matlab Descriptions)

关于PSO算法 ,这是一个与自适应控制有关,也是控制的输入.(On the PSO algorithm, which is a relevant and adaptive control as well as control input.)

觉得很好的一个Matlab程序想和大家一起分享，互相学习。(A Matlab program feel good and you want to share, learn from each other.)

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)

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is introduced by using the SVM. The kernel mapping idea is used to derive the non-linear version, Kernel Discriminant via Support Vectors (SVKD). In SVDA, only support vectors are involved to obtain the transformation matrix. Thus, the computational complexity can be greatly reduced for kernel based feature extraction. Experiments carried out on several standard databases show a clear improvement on LDA-based recognition

matlab的基础知识ppt04，适合初学者，希望大家好好学习(matlab basics ppt04, suitable for beginners, I hope you learn)

简单的matlab图像处理程序 以RGB颜色模型进行图像检测并包括颜色检测后腐蚀膨胀等滤波处理(Simple matlab image processing procedures to RGB color model testing and including color image after testing corrosion expansion filtering processing, etc )

matlab coade source for beam pattren for the simutalion of smart antenna in matlab