warning-modeling

说明：  基于matlab的双足机器人零动力学控制及其仿真，包括动力学及控制模块(Matlab biped robot based on the zero-dynamics control and simulation, including the dynamics and control module)

计算广义的hurst指数，本课题组编写程序，欢迎使用(compute general hurst, our group write program,welcome to use)

最优路径问题，蚁群算法,仓储系统的货位拣选路径优化仿真(Optimal path problem, ant colony algorithm, optimization simulation of cargo location picking path for warehouse system)

说明：  《MATLAB7.x与C/C++混合编程》配套的源程序 6.5.2节代码 vc.net通过扩展MFC动态链接库创建MEX程序(&quot MATLAB7.x and C/C++ mixed programming,&quot supporting the source code vc.net 6.5.2 MFC dynamic link library by extending the program to create MEX)

逐步判别分析的主函数 用于分类 [sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10) 输入变量 x为训练集.每行为一个样本，每列为一个变量. Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9] Test为待分类样本. 输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率. author 王新 2012.4.8 例子Sample: load fisheriris x=meas Class_x=[50,50,50] Test=meas(1:5,:) Fa1=4 [sel,c,c0,re,P]=StepclaassV2(x,Class_x,Test,Fa1)( Stepwise discriminant analysis for the classification of the main function [sel, c, c0, re, P] = StepclaassV2 (data, [50 50 50], data, 10) input variables x as the training set, each conduct a sample of each as a variable. Class_x, the classification for the training set, a row, the number of samples for all types, for example, [5 6 9] Test sample to be classified. output variable: sel for the selected variables serial number, c, c0 is fitted discriminant function. re discrimination results for the Test, P its posterior probability. author Wang 2012.4.8 examples Sample: load fisheriris x = meas Class_x = [50,50,50] Test = meas (1:5, :) Fa1 = 4 [sel, c, c0, re, P] = StepclaassV2 (x, Class_x, Test, Fa1))

MNF变换，能够实现高光谱遥感图像的MNF正逆变换，进行图像降维与重建(MNF transform, to achieve high spectral remote sensing images MNF inverse transform, image dimensionality reduction and reconstruction)

k-d树的matlab程序，包含了KDTREE, KDTREEIDX and KDRANGEQUERY functions。提供了两个Demo scripts(kdtree_demo.m & kdrange_demo.m),很实用( This distribution contains the KDTREE, KDTREEIDX and KDRANGEQUERY functions. Included are the source code files in kdtree/src, as well as precompiled mex files for the following systems: - Mac OS X (Matlab 6.5) - Redhat Linux (Matlab 6.5) - Windows (Matlab 6.1) Two demo scripts are provided (kdtree_demo.m & kdrange_demo.m). The new features added June 2004: + You can now use N dimensional data points, where N>3. + Use KDTREEIND to return the index value to the closest point, instead of the closest point values. + KDRANGEQUERY can now return these index values as well. Written by/send comments or suggestions to : Guy Shechter guy at jhu dot edu June 2004 )

he "while" loop uses a formula in ISSO, Chap. 10 the "identical" variable in the formula

EDGE PRESERVING SMOOTHING

matlab code for adaptive median filter