Bayes网络工具箱，可以用作分类或者拟和，希望对大家有用

ClustanGraphics聚类分析工具。提供了11种聚类算法。 Single Linkage (or Minimum Method, Nearest Neighbor) Complete Linkage (or Maximum Method, Furthest Neighbor) Average Linkage (UPGMA) Weighted Average Linkage (WPGMA) Mean Proximity Centroid (UPGMC) Median (WPGMC) Increase in Sum of Squares (Ward s Method) Sum of Squares Flexible (ß space distortion parameter) Density (or k-linkage, density-seeking mode analysis) -ClustanGraphics clustering analysis tools. Provides 11 kinds of clustering algorithms. Single Linkage (or Minimum Method, Nearest Neighbor) Complete Linkage (or Maximum Method, Furthest Neighbor) Average Linkage (UPGMA) Weighted Average Linkage (WPGMA) Mean ProximityCentroid (UPGMC) Median (WPGMC) Increase in Sum of Squares (Ward s Method) Sum of SquaresFlexible (? space distortion parameter) Density (or k-linkage, density-seeking mode analysis)

对于含有噪声的的数字图像模式“1、2、3、4”，使用“hopfield”神经网络，进行联想、识别，以去除噪声的影响。-for containing noise of the digital image model "1,2,3,4", "hopfield" neural network, Lenovo, identification, in order to remove noise impact.

bayes network classifier toolbox 贝叶斯网络分类器工具箱的bin文件-bayes network toolbox Bayesian classifier network classifier Toolbox for the paper bin

神经网络的HP算法，这是学习神经网络的入门课程．-HP neural network algorithm, which is learning neural network-oriented courses.

清华大学不确定规划教材中的模糊规划求解算法2-Tsinghua University, uncertainty in the planning of teaching materials fuzzy programming algorithm 2

很好用的一个适用程序，由Visual C＋＋编程，有收藏价值

Hopfield Model Autoassociative Memory 源码, 经典的HOPFIELD人工神经网络例子源码-Hopfield Model Autoassociative Memory source, HOPFIELD classic example of artificial neural network source

关于演化算法的小程序.以一个二元二次方程的求极值为例.对输入参数作了简化的固定处理.较好的说明了演化算法.可直接运行.-on evolutionary algorithm small procedures. A binary quadratic equation for the extreme example. To simplify the input parameters fixed address. A good note evolutionary algorithm. Direct operation.

图像检测模板匹配的Visual C++代码-Image Detection template matching Visual C code

我收集整理的有关于系统辨识的资料和一些方法的优缺点-I have collated the information on the system identification and the advantages and disadvantages of some methods