Automatic Detection of Solar Radio Spectrum Based on Codebook Model

Author:

Li Guoliang,Yuan Guowu,Zhou Hao,Wu Hao,Tan Chengming,Dong Liang,Gao Guannan,Wang Ming

Publisher

Springer Singapore

Reference16 articles.

1. Gao, G.N.: The Solar Radio Bursts and Fine Structuresin Metric and Decimetric Bands. University of Chinese Academy of Sciences (2015)

2. Ma, L., Chen, Z., Long, X., Yan, Y.: Multimodal deep learning for solar radio burst classification. Pattern Recogn. 61(1), 573–582 (2017)

3. Lobzin, V.V., Cairns, I.H., Robinson, P.A., et al.: Automatic recognition of type III solar radio bursts: automated radio burst identification system method and first observations. Space Weather-Int. J. Res. Appl. 7(4), S04002 (2009)

4. Lobzin, V.V., Cairns, I.H., Robinson, P.A., et al.: Automatic recognition of coronal type II radio bursts: the automated radio burst identification system method and first observations. Astrophys. J. Lett. 710(1), L58 (2010)

5. Zhang, P.J., Wang, C.B., Ye, L.: A type III radio burst automatic analysis system and statistic results for a half solar cycle with Nançay Decameter Array data. Astron. Astrophys. 618, A165 (2018)

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