一个简单的遗传算法 采用实数编码、比例分配轮盘赌选择、杂交采用离散与算术双重杂交、一般性变异。...

演化神经网络拓扑结构编写的扫雷机器人程序-evolution of neural network topology structure of the mine-sweeping robot procedures

基于神经网络的语音识别技术研究 基于神经网络的语音识别技术研究-Neural Network Based Speech Recognition Technology based on neural network speech recognition technology research

遗传算法优化小波神经网络的源程序,供研究设计使用-Genetic algorithm optimization of wavelet neural network source for research designed to use

exmat - The Expression Template Matrix Library,是矩阵运算模板库-exmat- The Matrix Expression Template Library, yes matrix calculation Template Library

BP神经网络用于函数拟合与模式识别的Matlab示例程序,说明很详细,并且代码可以直接拿来用-BP neural network for function fitting and pattern recognition procedures Matlab examples to illustrate in great detail, and the code can be directly used by

BugBots是一个游戏，描述它的最好方式是它是一个测试人工智能的框架。 来源: http://sourceforge.net/projects/bugbots/-BugBots is a game, describing it as the best method is that it is a test of artificial intelligence framework. Source : http://sourceforge.net/projects/bugbots/

Neural Networks ，8种神经网络，BP，RBF，CPN等通过VC++来实现了！-Neural Networks, 8 Neuro network, BP, RBF, CPN, such as through VC++ To achieve!

遗忘因子法递推算法用于估计数学模型的参数,精确度较高!-Forgetting factor recursive algorithm method used to estimate the parameters of the mathematical model, high accuracy!

一个可逆跳转蒙特卡罗采样（RJMCMC）算法详细程序，内附相关论文，对照论文看算法，便于理解。包含多种运动方式（增加，减少，分裂，合成，更新）-A Reversible Jump Monte Carlo sampling (RJMCMC) algorithm detailed procedures, enclosing the relevant papers, watch the control thesis algorithm, easy to understand. Contains a wide range of movement (increase, decrease, fragmentation, synthesis, update)

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.