Ordering of self-organizing maps in multidimensional cases

被引：7
|
作者：
Huang, GB [1 ]
Babri, HA [1 ]
Li, HT [1 ]
机构：
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 2263, Singapore
来源：
NEURAL COMPUTATION | 1998年 / 10卷 / 01期
关键词：
D O I：
10.1162/089976698300017872
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
It has been proved that in one-dimensional cases, the weights of Kohonen's self-organizing maps (SOM) will become ordered with probability 1; once the weights are ordered, they cannot become disordered in future training. It is difficult to analyze Kohonen's SOMs in multidimensional cases; however, it has been conjectured that similar results seem to be obtainable in multidimensional cases. In this note, we show that in multidimensional cases, even though the weights are ordered at some time, it is possible that they become disordered in the future.
引用
收藏
页码：19 / 23
页数：5
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