Abstract
Computation is applicable to any branch in order to improve performance in times of process and results improvement, this article is the demonstration of an automatic process applied to the area of astronomy. The classification of electromagnetic spectra by pattern recognition is based on an assembly composed of neighborhood-based methods of classification. The acquisition of the electromagnetic spectrum to classify, is obtained of the SDSS III (Sloan Digital Sky Survey), the process of classification consists of a preprocessing, to obtain a specific region of the spectrum followed by filtering in advance of relevant features by means of digital signal processing and the wavelet haar transform. abstract environment.
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Morales-Xicohtencatl, M., Flores-Pulido, L., Sánchez-Pérez, C.R., Córdova-Zamorano, J.J. (2014). RASCNA: Radio Astronomy Signal Classification through Neighborhood Assemblies. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_28
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DOI: https://doi.org/10.1007/978-3-319-12568-8_28
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