中文说明：
自组织神经网络概念和原理，并重点介绍一下自组织特征映射SOM网络。SOM和现在流行的ANN（MLP）模型在结构上类似，都由非常简单的神经元结构组成，但是SOM是一类“无监督学习”模型，一般的用法是将高维的input数据在低维的空间表示[1]，因此SOM天然是一种降维方法。除了降维，SOM还可以用于数据可视化，以及聚类等应用中。
English Description：
The concept and principles of self-organizing neural networks, with a focus on introducing self-organizing feature mapping SOM networks. SOM and the currently popular ANN (MLP) model are structurally similar, consisting of very simple neural structures. However, SOM is a type of "unsupervised learning" model, where high-dimensional input data is represented in low-dimensional space [1]. Therefore, SOM is naturally a dimensionality reduction method. In addition to dimensionality reduction, SOM can also be used in applications such as data visualization and clustering