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Sensors 2013, 13(8), 9604-9623; doi:10.3390/s130809604
Article

Low-Power Analog Processing for Sensing Applications: Low-Frequency Harmonic Signal Classification

1,* , 2
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 and 1
Received: 17 April 2013; in revised form: 17 July 2013 / Accepted: 22 July 2013 / Published: 25 July 2013
(This article belongs to the Section Physical Sensors)
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Abstract: A low-power analog sensor front-end is described that reduces the energy required to extract environmental sensing spectral features without using Fast Fouri´er Transform (FFT) or wavelet transforms. An Analog Harmonic Transform (AHT) allows selection of only the features needed by the back-end, in contrast to the FFT, where all coefficients must be calculated simultaneously. We also show that the FFT coefficients can be easily calculated from the AHT results by a simple back-substitution. The scheme is tailored for low-power, parallel analog implementation in an integrated circuit (IC). Two different applications are tested with an ideal front-end model and compared to existing studies with the same data sets. Results from the military vehicle classification and identification of machine-bearing fault applications shows that the front-end suits a wide range of harmonic signal sources. Analog-related errors are modeled to evaluate the feasibility of and to set design parameters for an IC implementation to maintain good system-level performance. Design of a preliminary transistor-level integrator circuit in a 0:µm complementary metal-oxide-silicon (CMOS) integrated circuit process showed the ability to use online self-calibration to reduce fabrication errors to a sufficiently low level. Estimated power dissipation is about three orders of magnitude less than similar vehicle classification systems that use commercially available FFT spectral extraction.
Keywords: Analog Harmonic Transform; classification; mixed-signal; low-power Analog Harmonic Transform; classification; mixed-signal; low-power
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

White, D.J.; William, P.E.; Hoffman, M.W.; Balkir, S. Low-Power Analog Processing for Sensing Applications: Low-Frequency Harmonic Signal Classification. Sensors 2013, 13, 9604-9623.

AMA Style

White DJ, William PE, Hoffman MW, Balkir S. Low-Power Analog Processing for Sensing Applications: Low-Frequency Harmonic Signal Classification. Sensors. 2013; 13(8):9604-9623.

Chicago/Turabian Style

White, Daniel J.; William, Peter E.; Hoffman, Michael W.; Balkir, Sina. 2013. "Low-Power Analog Processing for Sensing Applications: Low-Frequency Harmonic Signal Classification." Sensors 13, no. 8: 9604-9623.



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