Hyper sausage neuron: Recognition of transgenic sugar-beet based on terahertz spectroscopy

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• 作者：Jianjun Liu (1)
  Zhi Li (1) (2)
  Fangrong Hu (3)
  Tao Chen (3)
  Yong Du (4) (5)
  Haitao Xin (4)
  
  1. School of Mechano-Electronic Engineering ; Xidian University ; Xi鈥檃n ; Shanxi ; 710071 ; PR China
  2. Guilin University of Aerospace Technology ; Guangxi ; Guilin ; 541004 ; PR China
  3. School of Electronic Engineering and Automation ; Guilin University of Electronic Technology ; Guilin ; Guangxi ; 541004 ; PR China
  4. Shool of Information Engineering College ; Jimei University ; Xiamen ; Fujian ; 361005 ; PR China
  5. Xiamen University ; Xiamen ; Fujian ; 361005 ; PR China
  
• 刊名：Optics and Spectroscopy
• 出版年：2015
• 出版时间：January 2015
• 年：2015
• 卷：118
• 期：1
• 页码：175-180
• 全文大小：510 KB
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• 刊物类别：Physics and Astronomy
• 刊物主题：Physics
  Optical Spectroscopy and Ultrafast Optics
  Russian Library of Science
• 出版者：MAIK Nauka/Interperiodica distributed exclusively by Springer Science+Business Media LLC.
• ISSN：1562-6911

文摘

This paper presents a novel approach for identification of terahertz (THz) spectral of genetically modified organisms (GMOs) based on Hyper Sausage Neuron (HSN), and THz transmittance spectra of some typical transgenic sugar-beet samples are investigated to demonstrate its feasibility. Principal component analysis (PCA) is applied to extract features of the spectrum data, and instead of the original spectrum data, the feature signals are fed into the HSN pattern recognition, a new multiple weights neural network (MWNN). The experimental result shows that the HSN model not only can correctly classify different types of transgenic sugar-beets, but also can reject identity non similar samples in the same type. The proposed approach provides a new effective method for detection and identification of GMOs by using THz spectroscopy.