AddLabels

由matlab编译，一个很好的计算多重积分的模块。(From matlab compiler, a good module for calculating multiple integrals)

张正友摄像机标定matlab程序，用来求出摄像机的内外参数矩阵。(Zhang Zhengyou camera calibration matlab procedures used to calculate the camera' s internal and external parameter matrix.)

Tools for regression

这是一个基于matlab/RUNE环境的移动通信网络仿真程序包，用于科研或教学用途，可以仿真比较GPRS网络中的单播和组播的性能。(This is based on matlab/RUNE environment of mobile communication network simulation package, for scientific research or teaching purposes, you can compare unicast and multicast performance in GPRS network simulations.)

离散PID控制算法实例，matlab源程序(Discrete PID control algorithm instance, matlab source)

说明：  一维，二维，三维的各异向扩散滤波的matlab实现。(One-dimensional, two-dimensional, three-dimensional proliferation of different filter matlab to achieve.)

This is a MATLAB Simulation for obtaining conduction and switching losses in Three-Phase OHSW(optimized harmonic stepped wafeform) cascaded 9-level inverter.The simulation has been done in several SUBSYSTEMS.The first one produces switching functions based on OHSW.The second one is the 9-level inverter model.the third and fourth obtain load and switching devices currents respectively.The fifth and sixth obtain switching and conduction losses.

注意：本程序中，每点击一次“增加亮度”，图像灰度提升16；每点击一次“降低亮度”，图像灰度降低16。(Note : This procedure, every click an "increase in brightness," gray upgrade 16; Click on each of a "lower brightness," gray lower 16.)

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.)

The Sugeno-Takagi-like fuzzy controller: This controller is a two input one output fuzzy controller The first input is the error=x The second input is the error_dot=y(time derivative of the error) The output of the fuzzy controller is the CHANGE in the control action and NOT the control action.