Affiliation:
1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
2. Department of Computer Science and Engineering, Northeastern University, People's Republic of China
Abstract
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.
Subject
Cognitive Neuroscience,Arts and Humanities (miscellaneous)
Cited by
6 articles.
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