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Proceedings Paper

Neural network analysis of terahertz spectra of explosives and bio-agents
Author(s): Felipe Oliveira; Robert Barat; Brian Shulkin; John F. Federici; Dale Gary; David A. Zimdars
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Paper Abstract

A proposed, non-invasive, means to detect and characterize concealed biological and explosive agents in near real-time with a wide field-of-view uses spatial imaging of their characteristic transmission or reflectivity wavelength spectrum in the Terahertz (THz) electro-magnetic range (0.1-3 THz). Neural network analyses of the THz spectra and images will provide the specificity of agent detection and reduce the frequency of false alarms. Artificial neural networks are mathematical devices for modeling complex, non-linear functionalities. The key to a successful neural network is adequate training with known input-output data. Important challenges in the research include identification of the preferred network structure (e.g. multi-layer perceptron), number of hidden nodes, training algorithm (e.g. back propagation), and determination of what type of THz spectral image pre-processing is needed prior to application of the network. Detector array images containing both spectral and spatial information are analyzed with the aid of the Neurosolutions(TM) commercial neural network software package.

Paper Details

Date Published: 29 July 2003
PDF: 11 pages
Proc. SPIE 5070, Terahertz for Military and Security Applications, (29 July 2003);
Show Author Affiliations
Felipe Oliveira, New JerseyInstitute of Technology (United States)
Robert Barat, New Jersey Institute of Technology (United States)
Brian Shulkin, New Jersey Institute of Technology (United States)
John F. Federici, New Jersey Institute of Technology (United States)
Dale Gary, New Jersey Institute of Technology (United States)
David A. Zimdars, Picometrix, Inc. (United States)

Published in SPIE Proceedings Vol. 5070:
Terahertz for Military and Security Applications
R. Jennifer Hwu; Dwight L. Woolard, Editor(s)

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