Detail publikace

Piecewise-polynomial Signal Segmentation Using Reweighted Convex Optimization

NOVOSADOVÁ, M. RAJMIC, P.

Originální název

Piecewise-polynomial Signal Segmentation Using Reweighted Convex Optimization

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

We present a method for segmenting a one-dimensional piecewise polynomial signal corrupted by an additive noise. The method’s principal part is based on sparse modeling, and its formulation as a reweighted convex optimization problem is solved numerically by proximal splitting. The method solves a sequence of weighted `21-minimization problems, where the weights used for the next iteration are computed from the current solution.We perform experiments on simulated and real data and discuss the results.

Klíčová slova

proximal splitting algorithm; reweighted convex optimization; signal segmentation; signal smoothing; sparsity

Autoři

NOVOSADOVÁ, M.; RAJMIC, P.

Vydáno

7. 7. 2017

Místo

Barcelona

ISBN

978-1-5090-3981-4

Kniha

Proceedings of the 40th International Conference on Telecommunications and Signal Processing (TSP) 2017

Strany od

769

Strany do

774

Strany počet

6

BibTex

@inproceedings{BUT135481,
  author="Michaela {Novosadová} and Pavel {Rajmic}",
  title="Piecewise-polynomial Signal Segmentation Using Reweighted Convex Optimization",
  booktitle="Proceedings of the 40th International Conference on Telecommunications and Signal Processing (TSP) 2017",
  year="2017",
  pages="769--774",
  address="Barcelona",
  doi="10.1109/TSP.2017.8076092",
  isbn="978-1-5090-3981-4"
}