A sparse semi-blind source identification method and its application to Raman spectroscopy for explosives detection

Yuanchang Sun Jack Xin

Geometric Modeling and Processing mathscidoc:1912.43911

Signal Processing, 96, 332-345, 2014.3
Rapid and reliable detection and identification of unknown chemical substances are critical to homeland security. It is challenging to identify chemical components from a wide range of explosives. There are two key steps involved. One is a non-destructive and informative spectroscopic technique for data acquisition. The other is an associated library of reference features along with a computational method for feature matching and meaningful detection within or beyond the library.
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@inproceedings{yuanchang2014a,
  title={A sparse semi-blind source identification method and its application to Raman spectroscopy for explosives detection},
  author={Yuanchang Sun, and Jack Xin},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191224210608133438475},
  booktitle={Signal Processing},
  volume={96},
  pages={332-345},
  year={2014},
}
Yuanchang Sun, and Jack Xin. A sparse semi-blind source identification method and its application to Raman spectroscopy for explosives detection. 2014. Vol. 96. In Signal Processing. pp.332-345. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191224210608133438475.
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