一个简单的fisher分类器代码,并含有实验用的两个数据集合.

这是一个朋友做的人脸检测软件，是基于OpenCV 做的，很具有参考价值-This is a friend to do face detection software is based on OpenCV do, it is very valuable reference

人体运动检测与运动跟踪的源代码，用到了最新的算法，对这方面研究的人员很有帮助-Human Motion Detection and Motion Tracking source code, use the latest algorithms, this study helpful staff

使用Visual C++ 2003编写的遗传算法库，具有详细的说明文档，使用接口函数传入相关适应度函数与基因个数、迭代次数相关信息，进行目标优化，使用类模板的形式支持函数并行化-Using Visual C++ 2003 prepared by the genetic algorithm library, a detailed description of the document, use the interface function is passed the fitness function associated with the gene number, number of iterations relevant information to carry out objective optimization, the use of class template in the form of support function parallel

应用PCA（主成分分析）进行人脸识别的matlab程序，有较高成功率-PCA (Principal Component Analysis) face recognition Matlab procedures, which have a higher success rate

这是我自己花了很多时间写的一个BP神经网络类，里面封装了网络初始化、训练、分类等功能。奉献出来与感兴趣的朋友分享，绝对可靠。-that I spent a lot of time writing in a category BP neural network inside the network initialization package, training, classification capabilities. Dedication out with friends interested in sharing, absolutely reliable.

目标函数是De Jong函数，是一个连续、凸起的单峰函数-Objective function is De Jong function, is a continuous, convex function of the single-peak

这是一篇美国博士毕业设计的论文，是用神经网络实现mppt的方案-This is a graduation project of the United States, Dr. thesis, is to use neural network program to achieve MPPT

遗传算法解决随机期望值模型问题的例题-random genetic algorithms to solve the problem expectations model example

本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,

8皇后问题。所谓著名的八皇后问题就是八个皇后在8*8的网格中排列时不能同在一行、一列或者一条斜线上。根据前人的研究，在8！=40320种排列中只有92中解决方案。-8 Queen