Ballal-fuzzy-logic-notes

关于最优化算法的matlab 程序，搜索方向包括线性和非线性搜索(With regard to optimization algorithm matlab program, the search direction, including linear and nonlinear search)

很难得WEB。内部资料。初学者必看的，也是工程师们的良好的基础资料(A rare WEB. Internal data. Beginners a must-see, but also engineers a good basic information)

ADAPTIVETHRESHOLD An adaptive thresholding algorithm that seperates the foreground from the background with nonuniform illumination(ADAPTIVETHRESHOLD An adaptive threshold ing algorithm that separates the foreground fr om the background with nonuniform illuminatio n)

matlab自学经典教程，对初学者入门帮助较大(matlab self-classic guide more helpful to the beginner)

base implementation of MD4 family style digest as outlined in "Handbook of Applied Cryptography", pages 344 - 347.

Free Space Path Loss Model

matlab 30个经典案例分析，内容丰富经典，是初学者的好帮手(30 matlab classic examples)

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))

该matlab程序可以根据所选择的测试库中图片对人脸进行识别，从而在系统中找到与之匹配的图片。(The matlab program can test the library, the selected image on the human face recognition, which is found in the system to match the pictures.)

Map matching is the process of assigning user s location to the nearest node one a network. Three algorithms of map matching, point to point, point to line and line to line are presented in this document.