编程的 BP算法并行,很好,值得下载,详细的介绍了BP算法

遗传算法的VS2003工程，调试通过,An Introduction to Genetic Algorithms for Scientists and Engineers 书中的算法源程序-Genetic algorithm works VS2003, debugging through, An Introduction to Genetic Algorithms for Scientists and Engineers book algorithm source code

pso 粒子智能优化算法，C语言实现。欢迎下载。-Intelligent Optimization Algorithm pso particles, C language. Welcome to download

数据挖掘中很不错的源码,一个share算法的java源程序,有极好的可读性-data mining is a good source, a share algorithm java source files, has an excellent readability

用AMZI做的只能西湖地图，初学者做，人工智能-AMZI do with the only West Lake maps, beginners do, and artificial intelligence

svm_c 分类源码 用于svm的分类编程同svm_nu 相近-svm classification svm_c source for the classification of programming with similar svm_nu

LIBSVM源码。LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、 易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、 n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ） 等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM source. LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.

基于遗传算法的图像模式识别 ,这个是本人收藏的有关遗传算法的源程序-based on genetic algorithm for image pattern recognition, this is my collection of the genetic algorithm source code

神经网络模式识别及其实现，第三章。为大家提供参考。-pattern recognition and neural network to achieve, the third chapter. To provide a reference.

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

模式识别以及重要问题，很好的内容，千万不要错过-Pattern recognition, as well as important issues, very good content, do not miss