GrayGradinet

ct投影重建（shep-logan模型的生成投影以及重建）(ct projection reconstruction (shep-logan model for the generation of projection and reconstruction))

用Matlab语言编写的实现fisher准则，可以很方便的验证fisher准则(Fisher guidelines for implementation of the Matlab language, you can easily verify that the fisher criteria)

好用的图像融合代码，里面有两种融合规则。(image fusion)

MATLAB 编程有助于初学者进行学习，了解以及相应的运用(MATLAB programming will help beginners to learn, understand, and use of appropriate)

各种数字调制的一种产生方法，很有意思的哦......(A variety of digital modulation method for forming a very interesting ...... oh)

生成各种声速剖面数据，包括等声速，正负梯度声速，munk剖面，对称和反对称及跃层等。(Generate a variety of sound speed profile data, including sound velocity, etc., positive sound velocity gradient, negative sound velocity gradient, munk profile, symmetric, antisymmetric, thermocline and the like.)

直流电机的空载特性仿真程序，可以求电机的额定电动势(motor machine)

本程序仿真出了pH对象模型 并采用PID算法进行了控制 可以得出控制曲线(This procedure simulated the pH Object Model and PID algorithm, the control can draw the control curve)

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))

基于PCA的Isodata聚类算法matlab实现(Isodata algorithm based on PCA method)