title: [Describing language of spectra and rough set].
abstract: It is the traditional way to analyze spectra by experiences in astronomical field. And until now there has never been a suitable theoretical frame to describe spectra, which is may be owing to small spectra datasets that astronomers can get by low-level instruments. With the high-speed development of telescopes, especially on behalf of LAMOST, a large telescope which can collect more than 20,000 spectra in an observing night, spectra datasets are becoming larger and larger very fast. Facing these voluminous datasets, the traditional spectra-processing way simply depending on experiences becomes unfit. In this paper, we develop a brand-new language--describing language of spectra (DLS) to describe spectra of celestial bodies by defining BE (Basic element). And based on DLS, we introduce the method of RSDA (Rough set and data analysis), which is a technique of data mining. By RSDA we extract some rules of stellar spectra, and this experiment can be regarded as an application of DLS.
authors.affiliation: National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China.
authors.forename: Bo
authors.initials: B
authors.lastname: Qiu
authors.forename: Zhan-yi
authors.initials: ZY
authors.lastname: Hu
authors.forename: Yong-heng
authors.initials: YH
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001256:Astronomy / Q000379:methods* / Q000639:trends; D003627:Data Interpretation, Statistical; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D013057:Spectrum Analysis / Q000379:methods