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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