Detail publikace

Piecewise-polynomial signal segmentation using proximal splitting convex optimization methods

NOVOSADOVÁ, M. RAJMIC, P.

Originální název

Piecewise-polynomial signal segmentation using proximal splitting convex optimization methods

Typ

prezentace, poster

Jazyk

angličtina

Originální abstrakt

We show how the problem of segmenting noisy piecewise polynomial signal can be formulated as a convex optimization task. Because the number of model changes in signal is considered low in comparison to the overall number of data points, we rely on the concept of sparsity and its convex-relaxed counterpart, the l1-norm. We present an unconstrained, overparametrized optimization formulation whose solution can be used for detecting the breakpoints, and for robust data denoising, in consequence. The problem is solved numerically by iterative proximal splitting methods.

Klíčová slova

Signal segmentation; sparsity; convex optimization

Autoři

NOVOSADOVÁ, M.; RAJMIC, P.

Vydáno

8. 6. 2016

Strany od

1

Strany do

14

Strany počet

14

URL

http://www.utko.feec.vutbr.cz/~rajmic/talks/APMOD_2016-Novosadova.pdf

BibTex

@misc{BUT127474,
  author="Michaela {Novosadová} and Pavel {Rajmic}",
  title="Piecewise-polynomial signal segmentation using proximal splitting convex optimization methods",
  year="2016",
  pages="1--14",
  url="http://www.utko.feec.vutbr.cz/~rajmic/talks/APMOD_2016-Novosadova.pdf",
  note="presentation, poster"
}

Dokumenty

APMOD_2016-Novosadova.pdf