这是IBM公司使用的一个生成数据流的源文件代码，对需要生成数据流做实验的朋友很有帮助。...

基于CPN人工神经网络的例子，供大家交流-CPN-based artificial neural network example, for U.S. exchanges

一个聚类算法，这是清华大学电子系OCR实验室的人写的-a clustering algorithm, which is the Department of Electronics, Tsinghua University OCR laboratory wrote in the

迁移学习的经典文章，大多为国际顶级会议论文-Transfer of learning classic articles, most of the international top-level Conference Papers

HMM用于人脸识别，从OPENCV里提取出来的,非常经典的说-HMM for face recognition, OPENCV extract from the very classical said

用神经网络算法求解tsp问题。。。matlab编写。附有城市坐标用于检验。 -Using neural network algorithm for solving the problem tsp. . . matlab prepared. Coordinate with the city for inspection.

遗传算法（C++版），非常好的！-genetic algorithm (C version), very good!

BP神经网络VC类，此类对BP神经网络进行了封装，整个类是基于动态构建，可以适合于任何采用BP神经网络的模式识别应用。-BP neural network VC categories, such BP neural network to a package, the whole category is based on dynamic construction, and is suitable for use in any BP neural network applications of pattern recognition.

根据粒子群算法的特点，用vc写出了源程序，可以实现粒子群的优化-According to the characteristics of particle swarm optimization, using vc wrote source code, you can achieve the particle swarm optimization

小波神经网络，两者相互结合，程序简洁易懂！-Wavelet neural network, the two interact and procedures easier to understand!

基于单目手眼相机和激光测距仪，提出了一种尺寸未知的空间矩形平面的位姿测量算法。该算法不需要知道矩形平面 的G 个顶点的物体坐标，只需要知道它们的图像坐标、激光点的图像坐标和激光测距结果，就能够计算出尺寸未知空间矩形平 面在相机坐标系下的位姿，并且计算出矩形平面的尺寸。通过建立单目手眼相机和激光测距仪的数学模型，对该算法进行了验 证。实验结果表明，该算法是有效的，可以应用于机器人对空间物体的跟踪、定位以及抓取。-Monocular-based hand-eye cameras and laser range finder, a size of an unknown two-dimensional rectangular space Pose measurement algorithm. The algorithm does not need to know the G flat rectangular object vertex coordinates, they only need to know the image coordinates, image coordinates of laser points and the laser ranging results, we can calculate the size of the unknown space rectangular plane in the camera coordinate system bit posture, and to calculate the size of rectangular plane. Through the establishment of monocular hand-eye cameras and laser range finder of the mathematical model, the algorithm is verified. Experimental results show that the algorithm is effective, can be applied to the robot on the space object tracking, positioning, and crawling.