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Proceedings Paper

Application of support vector machines in the micro spectrometer
Author(s): Yuhong Xiong; Zhiyu Wen; Shaoping Xu; Famao Ye
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Paper Abstract

An important character of Micro Spectrometer with intelligence is that the spectrometer has the function of quickly qualitative analysis. The key of qualitative analysis is automatic spectral recognition technology. Though many efforts have been made, it is still not very satisfactory in practice because of small-sample and non-linearity of the spectral recognition problem. Support vector machines (SVM ) is gaining popularity as a simple and effective pattern recognition technique that can solve the small-sample and non-linearity learning problem better. The paper discusses support vector machines in the application of automatic spectral recognition, summarizes support vector machines method, puts forward a plan based on SVM and many features according to need of spectral recognition, builds basic model, gives a example to explain in the end.

Paper Details

Date Published: 18 May 2009
PDF: 5 pages
Proc. SPIE 7284, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Design, Manufacturing, and Testing of Micro- and Nano-Optical Devices and Systems, 72840V (18 May 2009); doi: 10.1117/12.832090
Show Author Affiliations
Yuhong Xiong, Nanchang Univ. (China)
Chongqing Univ. (China)
Zhiyu Wen, Chongqing Univ. (China)
Shaoping Xu, Nanchang Univ. (China)
Famao Ye, Nanchang Univ. (China)


Published in SPIE Proceedings Vol. 7284:
4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Design, Manufacturing, and Testing of Micro- and Nano-Optical Devices and Systems
Sen Han; Masaomi Kameyama; Xiangang Luo, Editor(s)

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