贝叶斯网络分类器的一点小程序，也许有用，请各位资源下载...

使用MATLAB6.5实现的自适应学习速率反向传播网络-Matlab6.5 achieved using adaptive learning rate back-propagation network

基本的神经网络计算TLU，对于所有学习神经归纳的第一个算法来说，单个神经容易做训练，虽然不会有问题的异或解，但它是人类神经史上的第一步。

Fast ICA，一种ICA的快速算法，有完整的论文（两种格式，pdf和ps的）-Fast ICA, the ICA a fast algorithm, a complete paper (both formats, pdf and ps)

径向基网络对Polynomial函数的逼近和拟合-Radial basis function networks Polynomial Approximation and fitting

基于MATLAB完成的神经网络源程序 大家-Based on the MATLAB neural network to complete the U.S. source

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.

遗传算法原程序，并行算法，原代码，随机搜索算法-GA original program, parallel algorithm, the original code, random search algorithm

this about the artificial neural networks which uses the back propogation method.-this is about the artificial neural networks which uses the back propogation method.

关于模式识别的经典书籍，英文版的，很值得看-On Pattern Recognition classic books, in English, is worth look

MIT大学的机器学习课程讲稿,很经典的!包括分类,回归,判别式学习,产生式学习,SVM等,基本上包括常用的机器学习算法-MIT University of speech machine learning curriculum, it is classic! Including classification, regression, discriminant study, resulting in learning, SVM, etc., basically including the commonly used machine learning algorithms