Piecewise-polynomial signal segmentation using proximal splitting convex optimization methods

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU119954" target="_blank" >RIV/00216305:26220/16:PU119954 - isvavai.cz</a>
Výsledek na webu
<a href="http://www.utko.feec.vutbr.cz/~rajmic/talks/APMOD_2016-Novosadova.pdf" target="_blank" >http://www.utko.feec.vutbr.cz/~rajmic/talks/APMOD_2016-Novosadova.pdf</a>
DOI - Digital Object Identifier
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Jazyk výsledku
angličtina
Název v původním jazyce
Piecewise-polynomial signal segmentation using proximal splitting convex optimization methods
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Piecewise-polynomial signal segmentation using proximal splitting convex optimization methods
Popis výsledku anglicky
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.

Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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