遗传算法源程序evolution calculates the law origin code ,C

这是马少平 朱小燕编著的人工智能配套课件，由清华大学出版社出版-This is Ma Shao-ping ZHU Xiao-yan matching artificial intelligence authoring courseware, from Tsinghua University Publishing House

该文档是清华大学的模式识别教程，该版本是网页版本，浏览非常方便，内容也非常详细，非常适合初学者，个人举得特别是支持向量机那一章描述很棒！-this document is from Tsinghua University,this is the html version,it is convenient to read, it is very suitable for the elementary readers,in my own opinion,the charter of svm is very detail and easily understandable.

该程序包主要讲述了遗传算法。文中的遗传算法是由C语言所编出来的。能够达到很好的优化效果。-The package focuses on the genetic algorithm. In this paper, genetic algorithm is made by the C language out. Optimized to achieve good effect.

关于人工神经网络的实用书籍，适合初学者，以及有一定基础的读者学习-Information on artificial neural networks and practical books, suitable for beginners, as well as readers of a certain basis for learning

模拟退火算法用于求解旅行商问题的matlab源程序-simulated annealing algorithm for solving the traveling salesman problem Matlab source

这是一个模式识别中的K均值算法的一个简单仿真分类实例，其中female.txt和male.txt是训练样本，test.txt是测试样本，分类效果非常好，对于模式学习的初学者将会有很大帮助。-This is a pattern recognition algorithm of the K-means classification of a simple simulation example is one of female.txt and male.txt training samples, test.txt is the measurement, classification effect is very good for beginners will be learning model has great help to me.

数据挖掘中的ID3算法源码 决策树的经典算法之一。 -Data Mining Source ID3 decision tree algorithm, one of the classic algorithm.

knn算法的实现，框架十分清楚。是经典的东西-KNN algorithm, the framework is very clear. Is a classic East-West

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. ~ ~ ..

This code in this directory implements the binary hopfield network.Source code may be found in HOPNET.CPP. A sample training file is H7x8N4.trn. Sample test pattern files are: H7x8D4.TST, H5x8D7.TST,H5x8D7.TST and H5x8D9.TST, Output of the program goes to both the screen and a file, ARCHIVE.LST.