Information-Theoretic Measures on Intrinsic Mode Function for the Individual Identification Using EEG Sensors

In spite of recent advances, the interest in extracting knowledge hidden in the electroencephalogram (EEG) signals is rapidly growing, as well as their application in the computational neuroengineering field, such as mobile robot control, wheelchair control, and person identification using brainwave...

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Veröffentlicht in:	IEEE sensors journal Jg. 15; H. 9; S. 4950 - 4960
Hauptverfasser:	Kumari, Pinki, Vaish, Abhishek
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.09.2015 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial Neural network Biometric Classification Data mining Decomposition EEG Electroencephalography Empirical Mode Decomposition (EMD) Entropy Feature extraction Fuzzy algorithm in LVQ learning vector quantization (LVQ-NN) Machine Learning Methods Neural networks Neurons Random variables Sensors artificial neural network learning vector quantization (LVQ-NN) and fuzzy algorithm in LVQ empirical mode decomposition (EMD) EEG Machine learning biometric
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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