This is a software written using MATLAB genetic algorithm procedure.

关联规则中的频繁项集生成算法genmax，可在linux和windows下编译运行，可能不太容易看懂。-association rules of frequent item sets genmax generation algorithm, and the Linux compiler running under windows, it may not be easy to understand.

林智仁编写的著名的SVM代码(libsvm-2[1]-林智仁prepared by well-known SVM code (libsvm-2 [1]

人脸检测源代码,是人工智能检索方面比较常用的,大家下班啊-Face Detection source code, artificial intelligence search area is relatively common, we work ah

基于股票的程序-Stock-based procedures

HOPFIELD的一个经典用例，解决TSP问题，代码完整，是我自己编写的哦-HOPFILED cases with a classic, TSP solution, code integrity, I was prepared oh

使用BP网络进行模式识别,识别0－9的数字-Using the BP network pattern recognition, identifying the number of 0-9

遗传算法的教材1-GA teaching a

自组织系统Kohonen网络模型。对于Kohonen神经网络，竞争是这样进行的：对于“赢”的那个神经元c，在其周围Nc的区域内神经元在不同程度上得到兴奋，而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程，经过一定次数的训练以后，网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构：它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ ..

在matlab6.5下实现的 -achieved in the matlab6.5

详细介绍了局部奇异值分解-details of local SVD