Parametric estimation of spectrum driven by an exogenous signal

Tom Dupré la Tour; Yves Grenier; Alexandre Gramfort

ICASSP 2017accepted0 citations

Parametric estimation of spectrum driven by an exogenous signal

Tom Dupré la Tour, Yves Grenier, Alexandre Gramfort

Abstract

In this paper, we introduce new parametric generative driven auto-regressive (DAR) models. DAR models provide a nonlinear and non-stationary spectral estimation of a signal, conditionally to another exogenous signal. We detail how inference can be done efficiently while guaranteeing model stability. We show how model comparison and hyper-parameter selection can be done using likelihood estimates. We also point out the limits of DAR models when the exogenous signal contains too high frequencies. Finally, we illustrate how DAR models can be applied on neuro-physiologic signals to characterize phase-amplitude coupling.

BibTeX

@inproceedings{icassp2017_parametricestima,
  title = {Parametric estimation of spectrum driven by an exogenous signal},
  author = {Tom Dupré la Tour and Yves Grenier and Alexandre Gramfort},
  booktitle = {ICASSP 2017},
  year = {2017}
}