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Clustering by SOM (Self-Organizing Maps) and MST (Minimal Spanning Tree)
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- IWAMOTO Kazuyuki
- Department of Electrical and Electronic Engineering, Tottori University
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- OBU-CANN OKwaw
- Department of Electrical and Electronic Engineering, Tottori University
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- TOKUTAKA Heizo
- Department of Electrical and Electronic Engineering, Tottori University
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- FUJIMURA Kikuo
- Department of Electrical and Electronic Engineering, Tottori University
Bibliographic Information
- Other Title
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- SOM(自己組織化マップ)とMST(最小結合木構造)によるクラスタ分類
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Description
Chemical spectra such as, AES (Auger Electron Spectroscopy), XPS (X-ray Photoelectron Spectroscopy), and XRD (X-Ray Diffraction) can be considered to be multi-dimensional information. They are mapped by using SOM and MST (Minimal Spanning Tree) methods. The units which are connected by MST are carefully observed among the compositions of 0-100% and all the OR combinations among the units selected. The classified results are compared with the clusters sorted by human eye in the SOM method.
Journal
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- IEICE technical report. Neurocomputing
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IEICE technical report. Neurocomputing 98 (674), 31-37, 1999-03-19
The Institute of Electronics, Information and Communication Engineers
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Details 詳細情報について
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- CRID
- 1573387452284314496
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- NII Article ID
- 110003233509
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- NII Book ID
- AN10091178
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- Text Lang
- ja
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- Data Source
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- CiNii Articles