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21 July 2017 A technique to identify some typical radio frequency interference using support vector machine
Yuanchao Wang, Mingtao Li, Dawei Li, Jianhua Zheng
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104200B (2017) https://doi.org/10.1117/12.2282039
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
Abstract
In this paper, we present a technique to automatically identify some typical radio frequency interference from pulsar surveys using support vector machine. The technique has been tested by candidates. In these experiments, to get features of SVM, we use principal component analysis for mosaic plots and its classification accuracy is 96.9%; while we use mathematical morphology operation for smog plots and horizontal stripes plots and its classification accuracy is 86%. The technique is simple, high accurate and useful.
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Yuanchao Wang, Mingtao Li, Dawei Li, and Jianhua Zheng "A technique to identify some typical radio frequency interference using support vector machine", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104200B (21 July 2017); https://doi.org/10.1117/12.2282039
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KEYWORDS
Mathematical morphology
Principal component analysis
Machine learning
Radio astronomy
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