该软件通过BP神经网络学习机制，能够对屏幕上的数字进行识别。...

米凯利维奇遗传算法-Mikerevic Genetic Algorithm

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.

TSP算法，应用局部搜索法得到最优路径，已经经过优化。没有密码，可以使用，vc环境下使用。-TSP algorithm, using local search to be optimal path has been optimized. No password can be used, vc environments.

Fuzzy logic controller that uses mamdani logic.

进化策略进行函数寻优Evolutionary function optimization strategy-Evolutionary function optimization strategy

最棒的三大计算机视觉、图像图形函数库之一，C语言版本，支持标准C-best of the three major computer vision, image and graphics functions, one C-language version supports standard C

基于C开发的三个隐层神经网络，输出权值、阈值文件，训练样本文件，提供如下函数：1）初始化权、阈值子程序；2）第m个学习样本输入子程序；3）第m个样本教师信号子程序；4）隐层各单元输入、输出值子程序；5）输出层各单元输入、输出值子程序；6）输出层至隐层的一般化误差子程序；7）隐层至输入层的一般化误差子程序；8）输出层至第三隐层的权值调整、输出层阈值调整计算子程序；9）第三隐层至第二隐层的权值调整、第三隐层阈值调整计算子程序；10）第二隐层至第一隐层的权值调整、第二隐层阈值调整计算子程序；11）第一隐层至输入层的权值调整、第一隐层阈值调整计算子程序；12）N个样本的全局误差计算子程序。-C development based on the three hidden layer neural network, the output weights, threshold documents, training sample documents, for the following functions : a) initialization, the threshold subroutine; 2) m learning samples imported subroutine; 3) m samples teachers signal Subroutine ; 4) hidden layer of the module input and output value subroutine; 5) the output layer of the module input and output value subroutine; 6) the output layer to the hidden layer subroutine error of generalization; 7) hidden layer to the input layer subroutine error of generalization; 8) the output layer to the third hidden layer Weight adjustment, the output layer threshold adjustment routines; 9) 3rd hidden layer t

离散二进制粒子群算法 DPSO -DPSO

用MATLAB语言编写。三十三座城市的蚂蚁算法。解决TSP问题。-Used MATLAB language. 33 cities in the ant algorithm. Solve the TSP problem.

提出了一种利用S函数实验结果表明：ICA可以将 脑电信号中包含的心电（ECG）、眼电（EOG）等多种干扰信号成功地分离出来-use of a S-function experimental results show : ICA EEG can be included in the heart (ECG), eyes (EOG) and other interference signal successfully separated