Skip to Main content Skip to Navigation
Conference papers

Ondelettes analytiques, application à l'analyse des processus multivariés à longue mémoire

Abstract : Multivariate processes with long-range dependent properties are found in a large number of applications including finance, geophysics and neuroscience. Statistical analysis of such data is challenging because multivariate time series present phase phenomenons. Analytic wavelets are well suited to deal with these characteristics. Our starting point is a paper of Selesnick which introduces quasi-analytic wavelets. We first establish the existence of these wavelets. We also give an exact formula quantifying their analytic quality. We then illustrate on simulations the relevance of quasi-analytic wavelets for multivariate time series analysis.
Document type :
Conference papers
Complete list of metadata

Cited literature [12 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01840082
Contributor : Irène Gannaz Connect in order to contact the contributor
Submitted on : Monday, July 16, 2018 - 12:48:04 PM
Last modification on : Wednesday, November 3, 2021 - 5:09:31 AM
Long-term archiving on: : Wednesday, October 17, 2018 - 2:17:22 PM

File

gretsi2017_OndelettesAnalytiqu...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01840082, version 1

Citation

Irène Gannaz, Sophie Achard, Marianne Clausel, François Roueff. Ondelettes analytiques, application à l'analyse des processus multivariés à longue mémoire. GRETSI 2017 - XXVIème Colloque francophone de traitement du signal et des images, Sep 2017, Juan-Les-Pins, France. ⟨hal-01840082⟩

Share

Metrics

Record views

167

Files downloads

178