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Process / pipelineTranslation-invariant wavelet decomposition

Maximal Overlap Discrete Wavelet Transform

Standardna DWT poduzorkuje nakon filtriranja, tako da pomak ulaza za jedan uzorak potpuno mijenja koji su koeficijenti različiti od nule – nije neovisna o pomaku. MODWT zadržava sve uzorke na svakoj skali podizorkovanjem filtara umjesto poduzorkovanja podataka. Ovo proizvodi N koeficijenata na svakoj skali (isto kao duljina ulaza), otkrivajući sve oscilacije bez obzira na njihovu vremensku fazu. To je poput korištenja finije vremenske rezolucije koja bilježi svako moguće poravnanje signala s valnim transformacijama.

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Izvori

  1. Percival, D. B., & Walden, A. T. (1995). Wavelet Methods for Time Series Analysis. Cambridge University Press. link
  2. Percival, D. B. (2000). Wavelet methods for time series analysis. Cambridge University Press. link
  3. Whitcher, B., Guttorp, P., & Percival, D. B. (2000). Wavelet analysis of covariance with application to atmospheric time series. Journal of Geophysical Research, 105(D11), 14941–14962. DOI: 10.1029/2000JD900110

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Maximal Overlap Discrete Wavelet Transform. ScholarGate. https://scholargate.app/hr/time-series/modwt

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ScholarGateMODWT (Maximal Overlap Discrete Wavelet Transform). Preuzeto 2026-06-15 s https://scholargate.app/hr/time-series/modwt · Skup podataka: https://doi.org/10.5281/zenodo.20539026