Orthogonality is superiority in piecewise-polynomial signal segmentation and denoising
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU130622" target="_blank" >RIV/00216305:26220/19:PU130622 - isvavai.cz</a>
Result on the web
<a href="https://asp-eurasipjournals.springeropen.com/articles/10.1186/s13634-018-0598-9" target="_blank" >https://asp-eurasipjournals.springeropen.com/articles/10.1186/s13634-018-0598-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1186/s13634-018-0598-9" target="_blank" >10.1186/s13634-018-0598-9</a>
Alternative languages
Result language
angličtina
Original language name
Orthogonality is superiority in piecewise-polynomial signal segmentation and denoising
Original language description
Segmentation and denoising of signals often rely on the polynomial model which assumes that every segment is a polynomial of a certain degree and that the segments are modeled independently of each other. Segment borders (breakpoints) correspond to positions in the signal where the model changes its polynomial representation. Several signal denoising methods successfully combine the polynomial assumption with sparsity. In this work, we follow on this and show that using orthogonal polynomials instead of other systems in the model is beneficial when segmenting signals corrupted by noise. The switch to orthogonal bases brings better resolving of the breakpoints, removes the need for including additional parameters and their tuning, and brings numerical stability. Last but not the least, it comes for free!
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/GA16-13830S" target="_blank" >GA16-13830S: Magnetic resonance perfusion imaging using compressed sensing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
EURASIP Journal on Advances in Signal Processing
ISSN
1687-6172
e-ISSN
—
Volume of the periodical
2019
Issue of the periodical within the volume
6
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
1-15
UT code for WoS article
000456723400001
EID of the result in the Scopus database
2-s2.0-85060729194