使用pca和svm方法对表情进行分类

lvq神经网络 的编程 希望大家能用的上-lvq neural network programming hope everyone can be on the

求最优值的一个算法-seeking an optimal value of the algorithm

一个径向网络算法程序!-a radial network algorithm!

DNA分类，包含三中模式识别经典算法的实现：K紧邻，BP神经网络，概率神经网络。-DNA classification, which includes three classic pattern recognition algorithm to achieve : K borders, BP neural networks, probabilistic neural network.

一个坦克大战的源码，适合VC初学者，希望对大家有所帮助！-a Tankedaizhan source code, suitable for beginners VC, and I hope to help you!

基于SVM，分本分类，，是关于两类分类的比较好的工具，国外网站提供，效果很好的-based SVM, the sub-classification is on the classification of the two types of relatively good tool, overseas sites provide good results, the

使用anfists的sugeno-type对混沌时间序列预测。-the use anfists Sugeno-type of chaotic time series prediction.

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.

以某区水文数据为例，在matlab7中构建BP神经网络，进行仿真预测。-Hydrological data in a certain district, for example, in matlab7 Building BP neural networks, simulation prediction.

Matlab implementation of ID3 and NaiveBayes classifier. It also includes example dataset as well.