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Automatic detection of solar radio burst using k-means clustering
Author(s): Zexiao Cui; Guowu Yuan; Guannan Gao; Liang Dong; Hao Zhou; Yun Gao; Shaojie Guo; Min Wang
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Paper Abstract

With the development of solar radio spectrometer, a large number of observational data has been obtained and the manual detection is difficult to reach the research needs. An automatic detection method of solar radio burst using kmeans clustering was presented in this paper. K-means clustering is introduced to classify the burst points in solar radio spectrum, and it can do better in high spectral and time resolution spectrometer. The experimental results show that the proposed method is effective.

Paper Details

Date Published: 14 August 2019
PDF: 8 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111793V (14 August 2019); doi: 10.1117/12.2539668
Show Author Affiliations
Zexiao Cui, Yunnan Univ. (China)
Guowu Yuan, Yunnan Univ. (China)
Guannan Gao, Yunnan Observatories (China)
Yunnan Univ. (China)
Liang Dong, Yunnan Observatories (China)
Yunnan Univ. (China)
Hao Zhou, Yunnan Univ. (China)
Yun Gao, Yunnan Univ. (China)
Shaojie Guo, Yunnan Observatories (China)
Yunnan Univ. (China)
Min Wang, Yunnan Observatories (China)
Yunnan Univ. (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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