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Plasmonic enhanced terahertz time-domain spectroscopy system for identification of common explosives

机译:等离子增强太赫兹时域光谱系统可识别常见爆炸物

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摘要

In this study, we present a classification algorithm for terahertz time-domain spectroscopy systems (THz-TDS) that can be trained to identify most commonly used explosives (C4, HMX, RDX, PETN, TNT, composition-B and blackpowder) and some non-explosive samples (lactose, sucrose, PABA). Our procedure can be used in any THz-TDS system that detects either transmission or reflection spectra at room conditions. After preprocessing the signal in low THz regime (0.1-3 THz), our algorithm takes advantages of a latent space transformation based on principle component analysis in order to classify explosives with low false alarm rate.
机译:在这项研究中,我们提出了太赫兹时域光谱系统(THz-TDS)的分类算法,该算法可以训练以识别最常用的炸药(C4,HMX,RDX,PETN,TNT,B成分和黑药)以及一些非爆炸性样品(乳糖,蔗糖,PABA)。我们的程序可用于任何在室温下检测透射光谱或反射光谱的THz-TDS系统。在对低THz范围(0.1-3 THz)的信号进行预处理之后,我们的算法利用了基于主成分分析的潜在空间变换的优势,可以对误报率较低的爆炸物进行分类。

著录项

  • 来源
    《Next-Generation Spectroscopic Technologies X》|2017年|1021012.1-1021012.6|共6页
  • 会议地点 Anaheim(US)
  • 作者单位

    Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey;

    Nanotechnology Research Center, Bilkent University, Ankara, Turkey;

    Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey,Nanotechnology Research Center, Bilkent University, Ankara, Turkey,Department of Physics, Bilkent University, Ankara, Turkey;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Terahertz; spectroscopy; classification; algorithm; explosive;

    机译:太赫兹光谱学分类;算法;炸药;

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