A Recurrent Quantum Neural Network model enhances the EEG signal for an improved Brain-computer interface

IET Seminar Digest

Volumn 2011, Issue 13611, 2011, Pages

  Gandhi, V ^a,b   Arora, V ^b   Behera, L ^a,b   Prasad, G ^a   Coyle, D H ^a   McGinnity, T M ^a  

^a UNIVERSITY OF ULSTER   (United Kingdom)

^b INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

Brain computer interface (BCI); Filter; Recurrent Quantum Neural Network (RQNN)

Indexed keywords

ASSISTIVE DEVICES; BRAIN SIGNALS; BRAIN-COMPUTER INTERFACES (BCI); CLASSICAL APPROACH; DATA SETS; DE-NOISING; EEG SIGNALS; FEATURE EXTRACTOR; FILTER; HUMAN MIND; INTELLIGENT INFORMATION PROCESSING; LINEAR DISCRIMINANT ANALYSIS; MENTAL PROCESS; MOTOR IMAGERY; POTENTIAL FIELD; PROBABILITY AMPLITUDE; PROBABILITY DENSITY FUNCTION (PDF); QUANTUM NEURAL NETWORKS; SCHRODINGER WAVE EQUATIONS; SELF ORGANIZED LEARNING;

BRAIN COMPUTER INTERFACE; METALS; NEURAL NETWORKS; SIGNAL DENOISING; WAVE PACKETS;

ELECTROENCEPHALOGRAPHY;

EID: 84860239927     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1049/ic.2011.0028     Document Type: Conference Paper

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