A multi-task learning approach for the extraction of single-trial evoked potentials

Computer Methods and Programs in Biomedicine

Volumn 110, Issue 2, 2013, Pages 125-136

  D'Avanzo, Costanza ^a   Goljahani, Anahita ^a   Pillonetto, Gianluigi ^a   De Nicolao, Giuseppe ^b   Sparacino, Giovanni ^a  

^a UNIVERSITY OF PADOVA   (Italy)

^b UNIVERSITY OF PAVIA   (Italy)

Author keywords

Bayesian estimation; Mixed effect models; Multilevel models; P300; Population approach; Single trial

Indexed keywords

BAYESIAN ESTIMATIONS; MIXED-EFFECT MODELS; MULTILEVEL MODEL; P300; POPULATION APPROACH; SINGLE-TRIAL;

BAYESIAN NETWORKS; ELECTROPHYSIOLOGY; REGRESSION ANALYSIS;

LINEARIZATION;

ACCURACY; ARTICLE; AVERAGING; BAYESIAN LEARNING; COGNITION; EVOKED RESPONSE; HUMAN; LEARNING; MULTI TASK LEARNING METHOD; NORMAL HUMAN; RECORDING; STOCHASTIC MODEL; TASK PERFORMANCE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; ELECTROENCEPHALOGRAPHY; EVENT-RELATED POTENTIALS, P300; EVOKED POTENTIALS; HUMANS; MODELS, THEORETICAL; REACTION TIME; SIGNAL PROCESSING, COMPUTER-ASSISTED; SOFTWARE; TIME FACTORS;

EID: 84875885465     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2012.11.001     Document Type: Article

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