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Detecting and Estimating Multivariate Self-Similar Sources in High-Dimensional Noisy Mixtures

Abry, Patrice and Wendt, Herwig and Didier, Gustavo Detecting and Estimating Multivariate Self-Similar Sources in High-Dimensional Noisy Mixtures. (2018) In: IEEE Workshop on statistical signal processing (SSP 2018), 10 June 2018 - 13 June 2018 (Freiburg, Germany).

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Official URL: https://doi.org/10.1109/SSP.2018.8450758

Abstract

Nowadays, because of the massive and systematic deployment of sensors, systems are routinely monitored via a large collection of time series. However, the actual number of sources driving the temporal dynamics of these time series is often far smaller than the number of observed components. Independently, self-similarity has proven to be a relevant model for temporal dynamics in numerous applications. The present work aims to devise a procedure for identifying the number of multivariate self-similar mixed components and entangled in a large number of noisy observations. It relies on the analysis of the evolution across scales of the eigenstructure of multivariate wavelet representations of data, to which model order selection strategies are applied and compared. Monte Carlo simulations show that the proposed procedure permits identifying the number of multivariate self-similar mixed components and to accurately estimate the corresponding self-similarity exponents, even at low signal to noise ratio and for a very large number of actually observed mixed and noisy time series.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org This papers appears in Proceedings of SSP 2018. Electronic ISBN: 978-1-5386-1571-3 The original PDF of the article can be found at: https://ieeexplore.ieee.org/document/8450758 Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
HAL Id:hal-02279354
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Ecole Normale Supérieure de Lyon - ENS de Lyon (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Université Claude Bernard-Lyon I - UCBL (FRANCE)
Other partners > Tulane University (USA)
Other partners > Université de Lyon - UDL (FRANCE)
Laboratory name:
Funders:
ANR : Agence nationale de la recherche (France) - ARO : Army Research Office (US)
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Deposited By: IRIT IRIT
Deposited On:23 Jul 2019 08:04

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