Ordering of Self-Organizing Maps in Multi-Dimensional Cases
نویسندگان
چکیده
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 difcult 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.
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ورودعنوان ژورنال:
- Neural Computation
دوره 10 شماره
صفحات -
تاریخ انتشار 1998