Signal Analysis Using Local Polynomial Approximations

Wildhaber, Reto; Ren, Elizabeth; Waldmann, Frédéric; Loeliger, Hans-Andrea (24 August 2020). Signal Analysis Using Local Polynomial Approximations 28th European Signal Processing Conference (EUSIPCO) Aug 2020.

[img] Text
0002239.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (445kB) | Request a copy

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.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

Engineering and Information Technology > Institute for Human Centered Engineering (HUCE)
Engineering and Information Technology > Institute for Human Centered Engineering (HUCE) > HUCE / HuCE - microLab
Engineering and Information Technology

Name:

Wildhaber, Reto0000-0002-0849-0775;
Ren, Elizabeth;
Waldmann, Frédéric and
Loeliger, Hans-Andrea

Subjects:

Q Science > QA Mathematics > QA75 Electronic computers. Computer science

Language:

English

Submitter:

Reto Wildhaber

Date Deposited:

09 Nov 2020 11:46

Last Modified:

14 Jan 2021 16:44

Uncontrolled Keywords:

localized polynomials, localized feature space, delay estimation, time-scale estimation, local signal approximation, autonomous linear state space models

ARBOR DOI:

10.24451/arbor.13181

URI:

https://arbor.bfh.ch/id/eprint/13181

Actions (login required)

View Item View Item
Provide Feedback