Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/103005
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Type: Journal article
Title: Terahertz signal classification based on geometric algebra
Author: Zhou, S.
Valchev, D.
Dinovitser, A.
Chappell, J.
Iqbal, A.
Ng, B.-.H.
Kee, T.
Abbott, D.
Citation: IEEE Transactions on Terahertz Science & Technology, 2016; 6(6):793-802
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Issue Date: 2016
ISSN: 2156-3446
2156-3446
Statement of
Responsibility: 
Shengling Zhou, Dimitar G. Valchev, Alex Dinovitser, James M. Chappell, Azhar Iqbal, Brian Wai-Him Ng, Tak W. Kee, and Derek Abbott
Abstract: This paper presents an approach to classification of substances based on their terahertz spectra. We use geometric algebra to provide a concise mathematical means for attacking the classification problem in a coordinate-free form. For the first time, this allows us to perform classification independently of dispersion and, hence, independently of the transmission path length through the sample. Finally, we validate the approach with experimental data. In principle, the coordinate-free transformation can be extended to all types of pulsed signals, such as pulsed microwaves or even acoustic signals in the field of seismology. Our source code for classification based on geometric algebra is publicly available at: https://github.com/swuzhousl/Shengling-zhou/blob/geometric-algebra- classifier/GAclassifier/.
Keywords: Classification; geometric algebra; multivectors; spectroscopy; terahertz (THz)
Rights: © 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
RMID: 0030057187
DOI: 10.1109/TTHZ.2016.2610759
Grant ID: http://purl.org/au-research/grants/arc/FT120100351
Appears in Collections:Electrical and Electronic Engineering publications

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