Signal Analysis Using Local Polynomial Approximations
Version
Published
Date Issued
2020-08-24
Author(s)
Type
Conference Paper
Language
English
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.
Subjects
QA75 Electronic computers. Computer science
Journal
28th European Signal Processing Conference (EUSIPCO) Aug 2020
Conference
28th European Signal Processing Conference (EUSIPCO) Aug 2020
Submitter
WildhaberR
Citation apa
Wildhaber, R., Ren, E., Waldmann, F., & Loeliger, H.-A. (2020). Signal Analysis Using Local Polynomial Approximations. In 28th European Signal Processing Conference (EUSIPCO) Aug 2020. 28th European Signal Processing Conference (EUSIPCO) Aug 2020. https://doi.org/10.24451/arbor.13181
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