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Detail publikačního výsledku
NOVOSADOVÁ, M.; RAJMIC, P.
Originální název
Piecewise-polynomial Signal Segmentation Using Reweighted Convex Optimization
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
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.
Anglický abstrakt
Klíčová slova
proximal splitting algorithm; reweighted convex optimization; signal segmentation; signal smoothing; sparsity
Klíčová slova v angličtině
Autoři
Rok RIV
2018
Vydáno
07.07.2017
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" }