通过MATLAB实现的打砖块游戏(breakout)，内含netlab人工神经网络工具箱...

用BP神经网络逼近函数Z=SIN(X*Y),采用C++编程.-Using BP neural network to approach the function Z = SIN (X* Y), using C++ programming.

一段采用BP神经网络算法的欠驱动机械臂平衡控制器的程序-Section of the use of BP neural network algorithm balance the underactuated manipulator controller procedures

这是神经网络和遗传算法想结合的c++程序，希望对需要的朋友 有所帮助。-This is a neural network and genetic algorithm would like to combine c++ Procedures, and they hope to help a friend in need.

PSO (粒子群优法)简单的范例程式 可以提供初学者使用-PSO (PSO You) simple programming model can provide beginners

很好的matlab模式识别工具箱，帮助大家建立典型的模式识别模式。-Good pattern recognition matlab toolbox to help the U.S. establish a typical pattern recognition model.

基于canny的灰色预测和模式识别,标定的一种做法是：在一块平板上画若干个点， 同时用这两部相机照相，分别得到这些点在它们像平面上的像点，利用这两组像点的几何关系就可以得到这两部相机的相对位置。然而，无论在物平面或像平面上我们都无法直接得到没有几何尺寸的“点”。实际的做法是在物平面上画若干个圆（称为靶标），它们的圆心就是几何的点了。而它们的像一般会变形，如图1所示，所以必须从靶标上的这些圆的像中把圆心的像精确地找到，标定就可实现。-Based on the gray canny prediction and pattern recognition, calibration approach is to: a plate painted in a number of points, at the same time with these two cameras camera, respectively, as these points in their plane as points, the use of these two groups geometric relationship between the image point can be that the relative positions of two cameras. However, in terms of objects such as plane or plane, we can not directly be no geometry point. Actual practice is complex plane painted in a number of round (known as targets), their geometric center of a circle is the point. And they generally like deformation, as shown in Figure 1, it must target these round, like in the center of a circle of like to find precise, calibration can achieve.

人工智能最大流算法 源码及设计文档，内含4个源代码-artificial intelligence maximum flow algorithm source code and design documents, containing four source code

遗传算法的四个源程序和源代码，在国内没有过的，看看国外的程序员是怎么编写的-Four genetic algorithm source code and source code, never at home and abroad to see how the programmer is prepared

人工智能神经网络识别 人工智能神经网络识别-Artificial neural network artificial neural network to identify

机器学习文本分类的SVM算法实现，VC++ 6.0环境下编译-A SVM algorithm for text classification in machine learning, and compiled under the Visual C++ 6.0 environment.