Signal analysis using local polynomial approximations
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Author (Corporation)
Publication date
2020
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Type
04B - Conference paper
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Parent work
2020 28th European Signal Processing Conference (EUSIPCO)
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DOI of the original publication
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Series number
Volume
Issue / Number
Pages / Duration
2239-2243
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Publisher / Publishing institution
IEEE
Place of publication / Event location
Amsterdam
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Abstract
Local polynomial approximations represent a versatile feature space for time-domain signal analysis. The parameters of such polynomial approximations can be computed by efficient recursions using autonomous linear state space models and often allow analytical solutions for quantities of interest. The approach is illustrated by practical examples including the estimation of the delay difference between two acoustic signals and template matching in electrocardiogram signals with local variations in amplitude and time scale.
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Subject (DDC)
Event
2020 28th European Signal Processing Conference (EUSIPCO)
Exhibition start date
Exhibition end date
Conference start date
18.01.2021
Conference end date
21.01.2021
Date of the last check
ISBN
978-9-0827-9705-3
978-9-08279-704-6
978-1-7281-5001-7
978-9-08279-704-6
978-1-7281-5001-7
ISSN
Language
English
Created during FHNW affiliation
No
Strategic action fields FHNW
Publication status
Published
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Peer review of the complete publication
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Closed
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Citation
Wildhaber, R., Ren, E., Waldmann, F., & Loeliger, H.-A. (2020). Signal analysis using local polynomial approximations. 2020 28th European Signal Processing Conference (EUSIPCO), 2239–2243. https://doi.org/10.23919/eusipco47968.2020.9287801