对一个具有150组80个元素的二进制输入矢量P，采用simal.m脚本文件进行自动分类的典型应用程序，其中取r=0.75，竞争层初始节点取10个，对ART1网络进行训练-Has 150 for a group of binary input vector P 80 elements, using simal. M scr ipt file for automatic classification of typical applications, including r = 0.75, the c

Hyperspectral image classification with limited number of labeled pixels is a challenging task. In this paper, we propose a bilayer graph-based learning framework to address this problem. For graph-based classification, how to establish the n