zuiyouhuaMatlab

说明：  一个关于KHA的算法，他是一种在KPCA基础上进一步训练的算法(a 5,500 on the algorithm, he is a KPCA in further training on the basis of the algorithm)

算术编码的matlab实现 ，便于无损压缩 (Arithmetic coding matlab implementation, ease of lossless compression)

说明：  tabu search for tsp by matlab

基于Matlab7.0的GPS数据分析程序，可以加载.txt格式的GPS数据，绘制出位置图形(The GPS data analysis based on Matlab7.0 program can be loaded. Txt format of GPS data, map out locations Graphic)

802.16eCTC的logmap算法仿真，MATLAB环境(802.16eCTC the logmap algorithm simulation, MATLAB environment)

Contains the matlab routines to estimate a univariate markov switching multifractal model of calvet and fisher 2004

bayes classifer,by taymaz farshi

The “INVERTED PENDULUM, ANALYSIS, DESIGN AND IMPLEMENTATION” is a collection of MATLAB functions and scripts, and SIMULINK models, useful for analyzing Inverted Pendulum System and designing Control System for it. This report & MATLAB-files collection are developed as a part of practical assignment on Control System Analysis, Design & Development practical problem. The assigned problem of INVERTED PENDULUM is a part of Lab Work of Control System – III Course at the INSTITUTE OF INDUSTRIAL ELECTRONICS ENGINEERING (IIEE), KARACHI, PAKISTAN

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))

k最近邻分类器。编写的一个matlab函数。输入向量Z表示所属的类，返回一个向量，表示由k最近邻分类给定的。(k nearest neighbor classifier. Write a matlab function. Input vector Z that belongs to the class, returns a vector, expressed by the k nearest neighbor classification given.)