1. 西安电子科技大学数学系,陕西,西安,710071
2. 中科院自动化所模式识别国家重点实验室,北京,100080
3. 西安电子科技大学数学系陕西西安,710071
4. 中科院自动化所模式识别国家重点实验室北京,100080
纸质出版:2005
移动端阅览
刘蓉, 段福庆, 刘三阳, 等. 基于小波特征的星系光谱分类[J]. 电子学报, 2005,33(11):2059-2062.
LIU Rong, DUAN Fu-qing, LIU San-yang, et al. Spectral Classification of Galaxy Based on Wavelet Feature[J]. Acta Electronica Sinica, 2005, 33(11): 2059-2062.
提出了一种新的星系光谱分类方法.首先
对原始光谱进行四级小波分解
选择主要包含谱线信息的第四级小波系数作为光谱的小波特征;然后
利用主分量分析对光谱的小波特征进行特征压缩
得到光谱的识别特征;最后
利用Fisher线性判别分析实现分类.该方法能够在红移值未知的情况下
对流量未定标的星系光谱进行识别.通过实验与其他几种分类方法进行了比较.实验结果表明
本文方法具有较强的鲁棒性
在流量未定标情况下的识别效果优于其他几种分类方法.
A technique for classification of galaxy spectra is proposed.At first
a four-level wavelet decomposition of the original spectrum is performed
and the wavelet coefficient at the fourth level
which mainly includes the information of spectral lines
is chosen as the wavelet feature of the spectrum.Secondly
principal components analysis is used to compress the wavelet feature and to get the recognition feature of the spectrum.Finally
Fisher linear discriminant analysis is employed for classification.This approach can recognize the galaxy spectrum whose flux is uncalibrated and redshift is unknown.Comparisons with several other classification techniques were made by experiments.Experiment results show the proposed method is robust and superior to other methods under the condition that flux is uncalibrated.
0
浏览量
1108
下载量
9
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621