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Fast Fourier Transform of non-periodic signals generated from a microplasma: migrating from a desktop computer to an IoT-connected smartphone
Author(s): Ryan Fitzgerald; Emily Wang; Vassili Karanassios
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Paper Abstract

There are many applications requiring an instrument to be brought to the sample for chemical analysis onsite (rather than bringing a sample to a lab for analysis, as is done traditionally). Ideally, for such applications, a portable chemical analysis instrument must be capable of acquiring data using a smartphone, have wireless capability and it must be able to become part of the Internet-of-Things (IoT). But do smartphones have the required processing power to execute computationally-intensive algorithms, such as a Fast Fourier Transform (FFT)? Among others, FFTs are used for filtering (e.g., de-noising) of periodic signals, thus improving Signal-to-Noise Ratio (SNR). Using non-periodic signals and Fourier-domain interpolation for resolution enhancement, it will be shown that smartphones do have the necessary power.

Paper Details

Date Published: 14 May 2018
PDF: 7 pages
Proc. SPIE 10657, Next-Generation Spectroscopic Technologies XI, 1065703 (14 May 2018); doi: 10.1117/12.2305462
Show Author Affiliations
Ryan Fitzgerald, Univ. of Waterloo (Canada)
Emily Wang, Univ. of Waterloo (Canada)
Vassili Karanassios, Univ. of Waterloo (Canada)


Published in SPIE Proceedings Vol. 10657:
Next-Generation Spectroscopic Technologies XI
Mark A. Druy; Richard A. Crocombe; Steven M. Barnett; Luisa T.M. Profeta; Abul K. Azad, Editor(s)

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