这个是脉冲耦合神经网络在边缘检测中的应用，脉冲耦合神经网络是第三代神经网络，天生就具有图像处理的优势。...

基于遗传算法的排课系统，可以实现多种课程的排列-based on genetic algorithm Course Scheduling System, can achieve a wide variety of courses with the

c语言神经网络程序包-neural network package

遗传算法MATLB图像分割程序及例子，希望对大家有用-GA MATLB procedures, there are genetic algorithm selection, crossover and mutation function, some simple examples MABTLAB GA!

Basic library that implements Kohonen s SOM and its learning. Lanuage: C# (.Net 3.5 Framework)

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. ~ ~ ..

贝叶斯学习算法分类文本。基于朴素贝叶斯分类器的文本分类的通用算法，是目前所知文本分类算法中最有效的一类-Bayesian text classification algorithm. Based on the simple Bayesian classifier of the definitive text classification algorithm, which is known text classification algorithm the most effective one category

isomap等规度映射，特征提取，机器学习-Isotacticity isomap mapping, feature extraction, machine learning

DBSCAN Designed by Dr. Michal aszykowski Department of Chemometrics Institute of Chemistry, The University of Silesia. It s the basic one.

基于自组织特征映射网络的聚类分析，是在神经网络基础上发展起来的一种新的非监督聚类方法，分析了基于自 组织特征映射网络聚类的学习过程，分析了权系数自组织过程中邻域函数和学习步长的一般取值问题，给出了基于自组织 特征映射网络聚类实现的具体算法，并通过实际示例测试，证实了算法的正确性。 -Based on self-organizing feature map network cluster analysis, neural network is developed on the basis of a new non-supervised clustering method, analysis based on self-organizing feature map network clustering of the learning process, analyzed the weights of self-organization the process of neighborhood function and learning step-size problem of the general values are given based on the self-organizing feature map network clustering algorithm to achieve concrete and practical examples of tests, confirmed the correctness of the algorithm.

pso智能算法程序，结合这个程序会对算法有更深的认识-intelligent algorithm PSO procedures, combined with this procedure will have a deeper understanding of algorithm