用C编写的遗传算法程序

人工智能课程中关于产生式系统部分上机实验的源代码，有很大参考价值。-No

Fuzzy logic controller that uses mamdani logic.

这个程序是在windows平台下运行game of life最好的平台。它不仅对细胞空间没有限制、运行速度非常快、界面很友好，而且能够为你提供大量的初始细胞分布图案，你还可以任意组合这些图案达到你象要的构形，然后让这些构形动起来组合出更加神奇的生命游戏的世界。-the procedure is the windows platform running game of life the best platform. It not only on the cell space is no restriction, running very fast, very friendly interface, but you have to provide a lot of initial cell distribution patterns, you can design any combination of these to you as to the configuration, then let these configuration movement combined to make life more wonderful game world.

不错的自组织神经网络算法，程序有注释。能运行，效果还行。-good self-organizing neural network algorithm, the procedure Notes. Can run, the results were OK.

本人编写的GramSchmidt神经网络算法，和传统的神经网络算法比较，该算法能自动产生神经元，节约时间，速度快！ 本人还加了自动产生分类的方法和适合各种函数的转换，该zip包括两个文件，一个是GramSchmidt正交分解，是个子函数，主函数是orth_GramSchmidt，放在同一目录下，就可运行，可以对benchmark的逼近和分类问题提供解决方案-I prepared GramSchmidt neural network algorithm, and the traditional neural network algorithm, the algorithm can automatically generate neurons, saving time, fast! I also added a method of automatically generated classification and conversion for a variety of functions, the zip includes two documents, one is GramSchmidt orthogonal decomposition is a sub-function, the main function is orth_GramSchmidt, on the same directory, you can run can benchmark approximation and classification problems to provide solutions

人脸检测定位的示例代码.rar VC++源码，具有一定参考价值,我也是从别处下载下来的。-Face Detection positioning the sample code. Rar VC source, which have a certain value, I also downloaded from the elsewhere.

SVM模式识别技术及在机械故障诊断中的应用进展-SVM pattern recognition technology and in Mechanical Fault Diagnosis of progress

使用C语言实现神经网络算法，针对BP神经网络的特点进行设计和开发，具有比较好的性能-use c language to develop neural network,good to use.

【全美经典】小波十讲（Ingrid Daubechies 著）中文版- [ Entire American classics ] wavelet ten lectures (Ingrid Daubechies) Chinese edition

〈智能优化算法与应用〉介绍各种优化算法：模拟褪火法、遗传算法、禁忌搜索法、神经网络法、混合优化策略等内容。-"intelligent optimization algorithms and application" on the various optimization algorithms : simulated fire faded, genetic algorithm, Tabu search method, neural networks, hybrid optimization strategy content.