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The Methods for Two-Dimensional Fiber Spectra Extraction

机译:二维纤维光谱提取方法

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Astronomy is an observation-based discipline which can obtain the important information about target stars by their spectrum. The two-dimensional fiber spectra contains abundant astrophysical information which plays an important role in the digital sky survey. But, the source observed data must be processed by several procedures before being used by astronomers, and spectra extraction is one of the important procedures. Meanwhile, it is well known that all images contain inherent uncertainty information, and fuzzy set theory is a powerful tool to describe and process such uncertainty, fuzzy regression is one of the important research topics which is used to set up the functional relationship between fuzzy variables. In this paper, we firstly review the existing spectra extraction methods, then discuss the fuzzy methods about spectra extraction, so can provide new ideas, new methods and new theoretical foundations for the processing methods about two-dimensional fiber spectra extraction.
机译:天文学是一门以观测为基础的学科,可以通过其光谱获得有关目标恒星的重要信息。二维纤维光谱包含丰富的天体信息,这些信息在数字天空勘测中起着重要作用。但是,源观测到的数据在被天文学家使用之前必须先经过几种程序处理,而光谱提取是重要的程序之一。同时,众所周知,所有图像都包含固有的不确定性信息,模糊集理论是描述和处理此类不确定性的有力工具,模糊回归是建立模糊变量之间的函数关系的重要研究课题之一。 。本文首先回顾了现有的光谱提取方法,然后讨论了光谱提取的模糊方法,从而为二维纤维光谱提取的处理方法提供了新的思路,新方法和新的理论基础。

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