Signal processing and machine learning for brain - machine interfaces. 

 - London, United Kingdom :  The institution of engineering and technology,  2018 
 - 340 p. ;  24x 16 cm 
<br/><br/> incluye índice 
<br/><br/>Brain - computer interfaces and electroencephalogram: basics and practical issues. -- Discriminative learning of connectivity patetern of motor imagery EEG. -- An experimental study to compare CSPand TSM techniques to extrac feactures during motor imagery tasks. -- Robust EEG signal processing with signal structures. -- A review transfer learning approaches in brain - computer interface. -- Unsupervised learning for brain - computer interfaces based on event - related potentials. -- covariate shift detection - based nonstationary adaptation in motor - imagery - based brain -- computer interface. -- A BCI challenge for the signal - processing community: considering the user in the loop. -- Feedforward artificial neural networks for event - related potential detection. -- Signal models for brain interfaces based on evoked response potential in EEG. -- Spatial filtering techniques for improving individual template - based SSVEP detection. -- A review of facture extraction and classification algorithms for image RSVP - based BCI. -- Decoding music perception and imagination using deep - learning techniques. -- Neurofeedback games using EEG- based brain - computer interface technology. 
<br/><br/><label>ISBN: </label>978-1-78561-398-2 (Pasta rústica) 
<br/><br/><label>Subjects--Topical Terms: </label><br/>TECNOLOGÍA MÉDICA<br/>INTERFACES CON EL USUARIO (COMPUTADORES)<br/>ELECTROENCEFALOGRAFÍA
<br/><br/><label>Dewey Class. No.: </label>006.31 S578s 2018