GA

说明：  超全的模式识别Matlab源程序，涉及几乎所有常见算法，还有图形界面，可以图形显示分析结果(Ultra-wide recognition of the Matlab source code, involving almost all the common algorithms, as well as a graphical interface, you can graph display the results of the analysis)

K-mean clustering. hope you enjoy

liquid level control using fuzzy logic controller

强大的matlab三维重建程序。对初学三维重建的人很好用。(An 3D reconstruction algorithm. You can run it. )

机器人路径规划；师兄做的一个程序，拿过来给大家分享；希望对大家有帮助；(Robot path planning 师兄to do a procedure, get back to everyone to share want to have to help everyone )

使用matlab调试C文件，mex相关操作。附带说明和源程序。(This code use matlab to debug the code which is writed by c.)

FCM算法的matlab实现，经典的FCM算法，使用IRIS数据(FCM algorithm matlab realize, classic FCM algorithm, the use of IRIS data)

Matlab的GUI中使窗口最大化，充满整个窗口(Matlab GUI to maximize window, full of the entire window )

在matlab中对服从威布尔分布的寿命数据进行尺寸、特征寿命、形状参数的估计。数据开始只用输入向量n的一组数就好了。(In matlab Weibull distribution of life data size, estimated lifetime characteristic shape parameters. Data starts with only a set number of input vectors n enough.)

此为模式识别中的Fisher线性判别方法求分类器。进行了男、女错误率和总错误率的统计。 全部程序流程如下： 1、读取FAMALE.TXT文件把身高或体重给数组，并求x1的样本均值m1和内离散度S1； 2、读取MALE.TXT文件把身高或体重给数组，并求x2的样本均值m2和内离散度S2； 3、求最佳变换向量和阀值点； 4、读取Test2.txt文件把对应的身高或体重给数组A并求A的样本数M； 5、把最佳变换向量和阀值点、x代入判别方程g（x）； 6、对本判别的错误率进行统计。(This is the pattern recognition method, to calculate the Fisher linear discriminant classifier .Were male , female and total error rate error rate statistics . All program flow is as follows : 1 , read FAMALE.TXT file to height or weight to the array, and find the sample mean m1 x1 and internal dispersion S1 2 , read MALE.TXT file to height or weight to the array, and find the sample mean m2 and x2 within the dispersion S2 3 , for the best transformation vector and the threshold point 4 , read Test2.txt file to the corresponding height or weight requirements for the array A and A is the number of samples M 5 , the best transformation vector and the threshold point , x substituted into the discriminant equation g (x) 6 , determine the error rate of the statistics . )