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Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor

Abstract : In this paper we aim to blindly calibrate a mobile sensor network whose sensor outputs and the sensed phenomenon are linked by a polynomial relationship. The proposed approach is based on a novel informed semi-nonnegative matrix factorization with a Vandermonde factor matrix. The proposed approach outperforms a matrix-completion-based method in a crowdsensing-like simulation of particulate matter sensing.
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https://hal.archives-ouvertes.fr/hal-01371239
Contributor : Matthieu Puigt <>
Submitted on : Saturday, September 24, 2016 - 11:24:23 PM
Last modification on : Tuesday, January 5, 2021 - 1:04:02 PM

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Clément Dorffer, Matthieu Puigt, Gilles Delmaire, Gilles Roussel. Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor. 9th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2016), Jul 2016, Rio de Janeiro, Brazil. ⟨10.1109/SAM.2016.7569735⟩. ⟨hal-01371239⟩

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