神经网络隐节点合成算法，用于神经网络泛化能力的提高，和大家共享！...

本程序利用遗传算法解决一简单的多项式极值问题-This procedure using the genetic algorithm to solve a simple problem of polynomial extremal

利用SOM（Self-Organization Map）数据聚类方法，包含点数据集的坐标，并以TChart分组为例进行说明。

自组织系统Kohonen网络模型。对于Kohonen神经网络，竞争是这样进行的：对于“赢”的那个神经元c，在其周围Nc的区域内神经元在不同程度上得到兴奋，而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程，经过一定次数的训练以后，网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构：它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ ..

基于遗传算法的基元识别与提取，C++源代码-Based on genetic algorithm identification and extraction of primitives, C++ Source code

Matlab implementation of ID3 and NaiveBayes classifier. It also includes example dataset as well.

遗传算法，通过选择、交叉、变异求取函数最优解c程序简单实现，并拥有最优保存思想。-Genetic algorithm, selection, crossover and mutation to strike a function of the optimal solution c procedures are simple to achieve, and has saved the best idea.

针对TSP问题，使用蚂蚁演算法求最佳解！程式还满美观唷！-against TSP, the use of the ant algorithm for the optimal solution! Program was one of appearance Police!

这是用Fortran实现的bp算法程序，供大家自学参-This is achieved using Fortran bp algorithm, for your self-Participation

利用双层感知器神经网络处理线性不可分的分类问题-use double perceptron neural networks to handle non-linear classification

4×4矩阵式键盘识别技术 * 注：为了有更多实用的实验程序供大家学习，部分程序参考网上的资源， * 在此谢谢这些无私奉献的朋友-4 × 4 matrix keyboard recognition technology* Note: in order to have more practical experimental procedures for everyone to learn some of the procedures refer to online resources,* thank these selfless dedication Friend