Detail publikace

Piecewise-polynomial Signal Segmentation Using Convex Optimization

RAJMIC, P. NOVOSADOVÁ, M. DAŇKOVÁ, M.

Originální název

Piecewise-polynomial Signal Segmentation Using Convex Optimization

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

A method is presented for segmenting one-dimensional signal whose independent segments are modeled as polynomials, and which is corrupted by additive noise. The method is based on sparse modeling, the main part is formulated as a convex optimization problem and is solved by a proximal splitting algorithm. We perform experiments on simulated and real data and show that the method is capable of reliably finding breakpoints in the signal, but requires careful tuning of the regularization parameters and internal parameters. Finally, potential extensions are discussed.

Klíčová slova

Signal segmentation, Denoising, Sparsity, Piecewise-polynomial signal model, Convex optimization

Autoři

RAJMIC, P.; NOVOSADOVÁ, M.; DAŇKOVÁ, M.

Vydáno

31. 12. 2017

Nakladatel

Institute of Information Theory and Automation of the ASCR

Místo

Prague

ISSN

0023-5954

Periodikum

Kybernetika

Ročník

53

Číslo

6

Stát

Česká republika

Strany od

1131

Strany do

1149

Strany počet

19

URL

https://www.kybernetika.cz/content/2017/6/1131

BibTex

@article{BUT138857,
  author="Pavel {Rajmic} and Michaela {Novosadová} and Marie {Mangová}",
  title="Piecewise-polynomial Signal Segmentation Using Convex Optimization",
  journal="Kybernetika",
  year="2017",
  volume="53",
  number="6",
  pages="1131--1149",
  doi="10.14736/kyb-2017-6-1131",
  issn="0023-5954",
  url="https://www.kybernetika.cz/content/2017/6/1131"
}