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

zbMATH Open1430.62228arXiv1407.1195MaRDI QIDQ5216381

Irène Gannaz

Publication date: 17 February 2020

Abstract: 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.

Full work available at URL: https://arxiv.org/abs/1407.1195

Mathematics Subject Classification ID

Functional data analysis (62R10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Biomedical imaging and signal processing (92C55)

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