Efficient initialization scheme for the self-organizing feature map algorithm

Mu Chun Su, Ta Kang Liu, Hsiao Te Chang

研究成果: 會議貢獻類型會議論文同行評審

23 引文 斯高帕斯(Scopus)

摘要

It is often reported in the technique literature that the success of the self-organizing feature map formation is critically dependent on the initial weights and the selection of main parameters of the algorithm, namely, the learning-rate parameter and the neighborhood function. In this paper, we propose an efficient initialization scheme to construct an initial map. We then use the self-organizing feature map algorithm to make small subsequent adjustments so as to improve the accuracy of the initial map. Two data sets are tested to illustrate the performance of the proposed method.

原文???core.languages.en_GB???
頁面1906-1910
頁數5
出版狀態已出版 - 1999
事件International Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
持續時間: 10 7月 199916 7月 1999

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???event.eventtypes.event.conference???International Joint Conference on Neural Networks (IJCNN'99)
城市Washington, DC, USA
期間10/07/9916/07/99

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