Classification of EEG recordings in auditory brain activity via a logistic functional linear regression model.

Irène Gannaz (1, 2)

1 ICJ - Institut Camille Jordan
2 GIPSA-lab - Grenoble Images Parole Signal Automatique

We want to analyse EEG recordings in order to investigate the phonemic categorization at a very early stage of auditory processing. This problem can be modelled by a supervised classification of functional data. Discrimination is explored via a logistic functional linear model, using a wavelet representation of the data. Different procedures are investigated, based on penalized likelihood and principal component reduction or partial least squares reduction.

Mots clés: auditory evoked potentials; phonemic identification; functional logistic linear model; wavelets; principal component reduction; LASSO penalization.; LASSO penalization

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Irène Gannaz. Classification of EEG recordings in auditory brain activity via a logistic functional linear regression model.. International Workshop on Functional and Operatorial Statistics, Jun 2014, Italy. p. 125-130. ⟨hal-00830313v2⟩