Detail publikace

Orthogonality is superiority in piecewise-polynomial signal segmentation and denoising

NOVOSADOVÁ, M. RAJMIC, P. ŠOREL, M.

Originální název

Orthogonality is superiority in piecewise-polynomial signal segmentation and denoising

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Segmentation and denoising of signals often rely on the polynomial model which assumes that every segment is a polynomial of a certain degree and that the segments are modeled independently of each other. Segment borders (breakpoints) correspond to positions in the signal where the model changes its polynomial representation. Several signal denoising methods successfully combine the polynomial assumption with sparsity. In this work, we follow on this and show that using orthogonal polynomials instead of other systems in the model is beneficial when segmenting signals corrupted by noise. The switch to orthogonal bases brings better resolving of the breakpoints, removes the need for including additional parameters and their tuning, and brings numerical stability. Last but not the least, it comes for free!

Klíčová slova

Signal segmentation; Signal smoothing; Signal approximation; Denoising; Piecewise polynomials; Orthogonality; Sparsity; Proximal splitting; Convex optimization

Autoři

NOVOSADOVÁ, M.; RAJMIC, P.; ŠOREL, M.

Vydáno

25. 1. 2019

Nakladatel

Springer Open

ISSN

1687-6172

Periodikum

EURASIP Journal on Advances in Signal Processing

Ročník

2019

Číslo

6

Stát

Spojené státy americké

Strany od

1

Strany do

15

Strany počet

15

URL

http://link.springer.com/article/10.1186/s13634-018-0598-9

Plný text v Digitální knihovně

http://hdl.handle.net/11012/137441

BibTex

@article{BUT153383,
  author="Michaela {Novosadová} and Pavel {Rajmic} and Michal {Šorel}",
  title="Orthogonality is superiority in piecewise-polynomial signal segmentation and denoising",
  journal="EURASIP Journal on Advances in Signal Processing",
  year="2019",
  volume="2019",
  number="6",
  pages="1--15",
  doi="10.1186/s13634-018-0598-9",
  issn="1687-6172",
  url="http://link.springer.com/article/10.1186/s13634-018-0598-9"
}