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Signal processing and machine learning for brain - machine interfaces.

Contributor(s): Material type: TextTextPublication details: London, United Kingdom : The institution of engineering and technology, 2018Description: 340 p. ; 24x 16 cmISBN:
  • 978-1-78561-398-2 (Pasta rústica)
Subject(s): DDC classification:
  • 006.31 S578s 2018
Contents:
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.
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Item type Current library Collection Call number Status Date due Barcode
Libro Libro Unicomfacauca Acervo general de Libros Available T05423

incluye índice

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.

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