expansion of Infomax algorithm, with a faster rate of convergence! The procedure...

神经网络BP算法-neural network algorithm

基于改进SVM的特征选择，可以帮助大家认识SVM-To improve the SVM-based feature selection can help you understand the SVM

基于BP算法的贝叶斯网络参数学习， 实现了图形话的节点表示和样本生成， 图形话的结果分析-BP algorithm based on Bayesian network parameter learning, the achievement of the graphics, then the node express and sample generation, if the results of graphical analysis

非线性程序之模式识别与控制系统设计.-nonlinear pattern recognition procedures and control system design.

神经网络与matlab实现,内含大量的实例,希望能对你有所帮助.-neural network and Matlab realized, with a lot of examples and I hope that you can help.

针对著名的UCI机器学习数据库中的iris data的kmeans聚类分析程序，具有代表性-For the well-known UCI machine learning repository of the iris data of kmeans cluster analysis procedure, a representative

改进遗传算法在TSP中的应用!很好用哦!-Improved Genetic Algorithm in TSP application! Good use Oh!

svm Main_SVR_Epsilon 用于svm回归的 在matlab中运用 -svm regression svm Main_SVR_Epsilon for use in matlab

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.-particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.