一篇研究遗传算法的人都必须看的文章，是国内遗传算法研究的泰斗！...

这一个指纹识别的源代码程序,相当有收藏价值-that a fingerprint identification of the source code procedures and very collectible value

实现了一个简单的花朵进化的模拟过程。 花朵的种群数量是10，共进化了50代。 -The realization of a simple simulation of the evolution of flowers. Flower populations is 10, a total of 50 on behalf of evolution.

遗传算法的实型表示实现，与大家共享一下。实际应用中只需改变evalF.m就可以-Genetic algorithm, said implementation of the real, to share with you about. Practical application can only change evalF.m

这是一本关于机器人硬件开发的书，本书的篇幅虽不太多，但很实用，内容为英文。-This is a book about the development of robotic hardware, books, the book" s length though not too much, but very practical, the content is English.

This code in this directory implements the binary hopfield network.Source code may be found in HOPNET.CPP. A sample training file is H7x8N4.trn. Sample test pattern files are: H7x8D4.TST, H5x8D7.TST,H5x8D7.TST and H5x8D9.TST, Output of the program goes to both the screen and a file, ARCHIVE.LST.

分类算法的研究很详细 很权威的 值得看看 有研究意义-Classification algorithm in detail to see if there should be a very authoritative research significance

可以用C++语言开发各种神经网络：BP，RBF，HOP~…………，使用前请看看说明文档，然后建立一个自己的项目文件，只要能明白作者的思路就能很方便地进行各种神经网络的设计，本人现在就在一个系统中使用它，目前这个开发包的版本已进入0.7了，但功能差不多，本人认为0.5这个版本用着也很方便，所以把他发来，大家共享。-C language can be used to develop a variety of neural networks : BP, RBF, HOP ~ ... ... please look at the use of pre-documented, and then the establishment of a project document, you will be able to understand the author"s ideas will be very convenient for the various neural network design, I in a system in which to use it, the current version of the development kit has entered 0.7, but the function almost, I think that this version of 0.5 is also very convenient, so he made to share.

基于神经网络的电离层F2层临界频率预测方法 基于神经网络的电离层F2层临界频率预测方法-Based on neural network of ionospheric layer F2 critical frequency forecasting methods based on neural network of ionospheric layer F2 critical frequency forecasting methods

关于matlab工具箱里的一些相关神经网络的程序-On the matlab toolbox, some related procedures for neural network

贝叶斯（Bayesion）机器学习相互信息。用于求取熵、联合熵等。改进后可用于随机反演-Bayesian (Bayesion) machine learning of mutual information. Used to obtain entropy, joint entropy and so on. Improved can be used for stochastic inversion