In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

Multiscale analysis of information dynamics for linear multivariate processes / Faes, L.; Montalto, A.; Stramaglia, S.; Nollo, G.; Marinazzo, D.. - ELETTRONICO. - 2016, 38th:(2016), pp. 5489-5492. (Intervento presentato al convegno Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) tenutosi a Orlando, FL, USA nel 16-20 Aug. 2016) [10.1109/EMBC.2016.7591969].

Multiscale analysis of information dynamics for linear multivariate processes

Faes L.;Nollo G.;
2016-01-01

Abstract

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.
2016
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Orlando, FL, USA
IEEE
Faes, L.; Montalto, A.; Stramaglia, S.; Nollo, G.; Marinazzo, D.
Multiscale analysis of information dynamics for linear multivariate processes / Faes, L.; Montalto, A.; Stramaglia, S.; Nollo, G.; Marinazzo, D.. - ELETTRONICO. - 2016, 38th:(2016), pp. 5489-5492. (Intervento presentato al convegno Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) tenutosi a Orlando, FL, USA nel 16-20 Aug. 2016) [10.1109/EMBC.2016.7591969].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/294316
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 6
social impact