Using SOM (Self

介绍了神经 网络中的CPN算法的C语言实现.-Introduce a neural network algorithm in C language CPN realize.

谢大同郭涛算法(函数优化)源代码下载，和大家分享自己的东西-Xie Datong Guo Tao algorithm (function optimization) source code download, and share things on your own

Mining sequential patterns with constraint (SPADE with constraint)

基于神经网络的汉语语音情感识别的研究。很好的描述了人工神经网络的方面-Neural Network Based Speech Emotion Recognition in Chinese studies. Good description of the artificial neural network connection

这是关于人工神经网络的c算法实现，对于算法研究比较有用！-C++ implementation of class network By Luca Cinti and Lorenzo Masetti, based on lightweight neural net library written in C by Peter van Rossum.

BP神经网络用于函数拟合与模式识别的Matlab示例程序,说明很详细,并且代码可以直接拿来用-BP neural network for function fitting and pattern recognition procedures Matlab examples to illustrate in great detail, and the code can be directly used by

最新开发的小波融合算法实现VC程序。非常好用。-latest development of the wavelet algorithm VC fusion procedures. Very handy.

一个简单的遗传算法源代码。。。。。代码保证尽可能少，实际上也不必查错-A simple genetic algorithm source code. . . . . Code to ensure that as little as possible, in fact, do not have error checking

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

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