Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloOn the Potential of Time Delay Neural Networks to Detect Indirect Coupling between Time Series
Anno di pubblicazione2020
Autore/iRossi Riccardo; Murari Andrea; Gaudio Pasquale
Affiliazioni autori1,3: Department of Industrial Engineering, University of Rome "Tor Vergata", via del Politecnico 1, 00100 Roma, Italy; 2 : Consorzio RFX (CNR, ENEA, INFN, Universita di Padova, Acciaierie Venete SpA), Corso Stati Uniti 4, 35127 Padova, Italy.
Autori CNR e affiliazioni
  • inglese
AbstractDetermining the coupling between systems remains a topic of active research in the field of complex science. Identifying the proper causal influences in time series can already be very challenging in the trivariate case, particularly when the interactions are non-linear. In this paper, the coupling between three Lorenz systems is investigated with the help of specifically designed artificial neural networks, called time delay neural networks (TDNNs). TDNNs can learn from their previous inputs and are therefore well suited to extract the causal relationship between time series. The performances of the TDNNs tested have always been very positive, showing an excellent capability to identify the correct causal relationships in absence of significant noise. The first tests on the time localization of the mutual influences and the effects of Gaussian noise have also provided very encouraging results. Even if further assessments are necessary, the networks of the proposed architecture have the potential to be a good complement to the other techniques available in the market for the investigation of mutual influences between time series.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da584-1
Pagine a584-12
Pagine totali12
RivistaEntropy (Basel, Online)
Attiva dal 1999
Editore: MDPI, - Basel
Lingua: inglese
ISSN: 1099-4300
Titolo chiave: Entropy (Basel, Online)
Titolo proprio: Entropy. (Basel, Online)
Titolo abbreviato: Entropy (Basel, Online)
Numero volume della rivista22
Fascicolo della rivista5
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ResearchGate (Codice:341559686)
  • Scopus (Codice:2-s2.0-85085768921)
  • ISI Web of Science (WOS) (Codice:000541900700040)
Parole chiavetime series, indirect coupling, time delay neural networks, Lorenz system
Link (URL, URI)
Titolo parallelo-
Scadenza embargo-
Data di accettazione19/05/2020
Note/Altre informazioniArticle Number: 584
Strutture CNR
  • ISTP — Istituto per la Scienza e Tecnologia dei Plasmi
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
On the Potential of Time Delay Neural Networks to Detect Indirect Coupling between Time Series (documento privato )
Descrizione: L'allegato contiene l'articolo così come pubblicato. / The Annex contains the Article as published.
Tipo documento: application/pdf