支持向量机源码，vc编写，对于svm初学者非常使用非常方便

神经网络蚁群算法，共三段，非常有用，快来下啊-Ant colony algorithm for neural networks, a total of three sections, very useful

真正可以用的匈牙利算法 我校赛的时候用过 很不错 不过写的不够简洁-Really can use the Hungarian algorithm school tournament when I used is pretty good but not enough to write a concise

本程序实现通过构造一棵前缀树实现 最大模式频繁项集挖掘算法.应用fp树增长算法实现.-the program by constructing a prefix tree to achieve the greatest model Frequent Mining algorithms. Application fp growth tree algorithm.

Lin-Kernighan聚类算法源代码，下载后可以直接编译执行-Lin-Kernighan clustering algorithm source code, download directly to compile the implementation of

MATHEMATICA 软件运用 The biggest similarity for tsp-MATHEMATICA software to use The biggest similarity for tsp

西安电子科技大学模式识别原理与应用课件1-Xi" an University of Electronic Science and Technology Pattern Recognition Theory and Application of a courseware

在matlab 环境下用遗传算法求解TSP问题。包含源代码和说明文档-In the matlab environment using genetic algorithm TSP problem. Contains the source code and documentation

Vc++下如何利用Matlab工具箱进行数字信号处理-Vc++ How to use Matlab toolbox for digital signal processing

这是我自己做的改进的遗传算法，主要是克服遗传算法的早熟问题-This is what I want done to improve the genetic algorithm, which is aimed at overcoming the genetic algorithm early problems

2。《遗传算法――理论、应用与软件实现》，王小平、曹立明编着 西安交通大学出版社 2002年第一版 本书全面系统地介绍了遗传算法的基本理论，重点介绍了遗传算法的经典应用和国内外的新发展。全书共分11章。第1章概述了遗传算法的产生与发展、基本思想、基本操作以及应用情况；第2章介绍了基本遗传算法；第3章论述了遗传算法的数学基础；第4章分析了遗传算法的多种改进方法；第5章初步介绍了进货计算理论体系；第6章介绍了遗传算法应用于数值优化问题；第7章介绍了遗传算法应用于组合优化问题；第8章介绍了遗传算法应用于机器学习；第9章讨论了遗传算法在智能控制中的应用；第10章讨论了遗传算法与人工生命研究的相关问题；第11章介绍了遗传算法在图像处理、模式识别中的应用。-2. "Genetic Algorithm-- theory, application and software," Wang Xiaoping, Li-Ming Cao compile Xi"an Jiaotong University Press in 2002 the first book version of the comprehensive and systematic introduction of the genetic algorithm"s basic On focuses on the classical genetic algorithm use and the new development. The book is divided into 11 chapters. Chapter 1 provides an overview of the genetic algorithm for the selection and development of basic ideas, basic operation and the application; Chapter 2 introduces the basic genetic algorithms; Chapter 3 of the genetic basis of a mathematical algorithm; Chapter 4 Analysis of the genetic algorithm app