Outlier Detection from Non-Smooth Sensor Data

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A4 Artikkeli konferenssijulkaisussa
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Date

2019-09-05

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Department of Computer Science

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Language

en

Pages

5

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EUSIPCO 2019 - 27th European Signal Processing Conference, pp. 1-5, European Signal Processing Conference

Abstract

Outlier detection is usually based on smooth assumption of the data. Most existing approaches for outlier detection from spatial sensor data assume the data to be a smooth function of the location. Spatial discontinuities in the data, such as arising from shadows in photovoltaic (PV) systems, may cause outlier detection methods based on the spatial smoothness assumption to fail. In this paper, we propose novel approaches for outlier detection of non-smooth spatial data. The methods are evaluated by numerical experiments involving PV panel measurements as well as synthetic data.

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Keywords

outlier detection, spatial signals

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DOI

10.23919/EUSIPCO.2019.8903061

Citation

Huuhtanen, T, Ambos, H & Jung, A 2019, Outlier Detection from Non-Smooth Sensor Data. in EUSIPCO 2019 - 27th European Signal Processing Conference. European Signal Processing Conference, IEEE, pp. 1-5, European Signal Processing Conference, Coruna, Spain, 02/09/2019. https://doi.org/10.23919/EUSIPCO.2019.8903061

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https://urn.fi/URN:NBN:fi:aalto-202001021421

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[article-cris] Perustieteiden korkeakoulu / SCI