Kohonen神经网络算法工作机理为：网络学习过程中，当样本输入网络时，竞争层上的神经元计算输入样本与竞争层神经元权值之间的欧几里德距离，距离最小的神经元为获胜神经元。调整获胜神经元和相邻神经元权值，使获得神经元及周边权值靠近该输入样本。通过反复训练，最终各神经元的连接权值具有一定的分布，该分布把数据之间的相似性组织到代表各类的神经元上，使同类神经元具有相近的权系数，不同类的神经元权系数差别明显。需要注意的是，在学习的过程中，权值修改学习速率和神经元领域均在不断较少，从而使同类神经元逐渐集中。-Kohonen neural network algorithm for the working mechanism: the network learning process, when the samples enter the network, the competitive layer of neurons on the calculation of input samples and competitive layer neurons Euclidean distance between the weights from the smallest neurons Winning neuron. Adjust the winning neuron and neighboring neurons weights to gain weight and peripheral neurons close to the input samples. Through repeated training, and ultimately the connection weights of neurons with a certain distribution, the distribution of the similarity between the data to representatives of organizations of various types of neurons, so that similar neurons have similar weights, different types of nerve Element obviously different weights. Note that, in the learning process, the right to modify the value of the field of learning rate and neurons were constantly low, so that the same neurons gradually concentrated.