A Method for Auto-Recognizing the M-type Stars Based on Wavelet Feature

LIU Zhong-tian; LI Xiang-ru; WU Fu-chao; ZHAO Yong-heng

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A Method for Auto-Recognizing the M-type Stars Based on Wavelet Feature

更新时间：2025-07-16

- A Method for Auto-Recognizing the M-type Stars Based on Wavelet Feature
- Acta Electronica Sinica Vol. 35, Issue 1, Pages: 157-160(2007)
- 作者机构：
  
  1. 北京交通大学电子信息工程学院,北京,100044
  2. 中国科学院自动化研究所模式识别国家重点实验室,北京,100080
  3. 中国科学院国家天文台,北京,100012
  4. 北京交通大学电子信息工程学院北京,100044
  5. 中国科学院自动化研究所模式识别国家重点实验室北京,100080
  6. 中国科学院国家天文台北京,100012
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.7
- Published：2007
- 稿件说明：
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LIU Zhong-tian, LI Xiang-ru, WU Fu-chao, et al. A Method for Auto-Recognizing the M-type Stars Based on Wavelet Feature[J]. Acta Electronica Sinica, 2007, 35(1): 157-160.
DOI：

LIU Zhong-tian, LI Xiang-ru, WU Fu-chao, et al. A Method for Auto-Recognizing the M-type Stars Based on Wavelet Feature[J]. Acta Electronica Sinica, 2007, 35(1): 157-160. DOI：

摘要

M型星对研究恒星的演化具有重要价值.在我国正在实施的大型巡天项目(LAMOST项目)中

急需M型星的自动识别系统.本文给出了一种自动识别M型星的新方法

该方法由以下主要步骤组成:①选取一定波长范围的光谱进行5层小波变换

从第5层小波系数中提取出小波特征;②利用小波特征检测M型星特征频率和吸收带位置;③根据特征频率和吸收带位置的检测结果进行M型星识别.大量真实光谱数据实验表明

本文方法十分有效

识别率高达97.56%.

Abstract

M-type stars play a significant role in the study of star evolution.The LAMOST project

the largest sky survey project being implemented in China

urgently needs a system for auto-recognizing M-type stars.This paper presents a novel method that can automatically recognize M-type stars.This method consists of three main steps:First

after a wavelet transform with 5 scales on the spectra in a selected wavelength region

the wavelet features are extracted from the transformed coefficients on the 5th scale.Then

the characteristic frequency of M-type stars and the locations of absorption bands are obtained accurately through the wavelet features.Finally

based on the results of the former step

M-type stars in all kinds of celestial bodies can be recognized.The extensive experiments with real observed spectra show that the proposed method is effective and the correct rate of this method is as high as 97.56%.

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