RBFclassification

MATLAB的一些例程，很好很实用。一百例(MATLAB some routines, good practical. 100 cases)

拟合直线拟合直线拟合直线拟合直线拟合直线拟合直线拟合直线拟合直线拟合直线拟合直线(polyfit the line polyfit the line polyfit the line)

线性调频信号的灵巧噪声卷积干扰matlab实现(Chirp signal dexterity the noise convolution interference matlab achieved)

This example shows how to calculate the deflection of a structural plate acted on by a pressure loading using the Partial Differential Equation Toolbox(TM).

sieve analysis program matlab code

Programa que calcula as curvas de I x v e potencia de PV solar

Poer spectral density of BPSK, QPSK and 16-QAM

说明：   实例讲解最小二乘法汇总及matlab仿真学习实例的源程序(matlab )

间歇反应釜的matlab建模，M文件，c可自由改变(Modeling of batch reactor)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)