Published by LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
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Published by LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
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Published by LAP Lambert Academic Publishing, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
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Published by LAP Lambert Academic Publishing 2013-04, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
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Published by LAP LAMBERT Academic Publishing, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
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Published by LAP Lambert Academic Publishing 10/24/2011, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
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Paperback or Softback. Condition: New. Wavelet-Fractal & Neuro-Fuzzy for Brain Computer Interface Application 0.36. Book.
Published by LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
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Published by LAP LAMBERT Academic Publishing Apr 2013, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -1. In this book, a novel brain-computer interface (BCI) system is proposed to analyze motor imagery (MI) electroencephalogram (EEG) signals. 2. After eliminating EOG artifacts automatically and extracting features by wavelet-based phase synchronization approach, support vector machine (SVM) is adopted for the classification of single-trial left and right MI data. 3. The EOG artifacts are automatically removed by means of modified independent component analysis (ICA). 4. The features are extracted from wavelet data by phase synchronization, and then classified by the SVM. 5. Compared with the results without EOG artifact removal, spectral band and AR model features, the proposed system achieves satisfactory results in BCI applications. 52 pp. Englisch.
Published by LAP LAMBERT Academic Publishing, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by LAP Lambert Academic Publishing, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
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Published by LAP Lambert Academic Publishing 2011-10, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
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Published by LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 1. In this book, a novel brain-computer interface (BCI) system is proposed to analyze motor imagery (MI) electroencephalogram (EEG) signals. 2. After eliminating EOG artifacts automatically and extracting features by wavelet-based phase synchronization approach, support vector machine (SVM) is adopted for the classification of single-trial left and right MI data. 3. The EOG artifacts are automatically removed by means of modified independent component analysis (ICA). 4. The features are extracted from wavelet data by phase synchronization, and then classified by the SVM. 5. Compared with the results without EOG artifact removal, spectral band and AR model features, the proposed system achieves satisfactory results in BCI applications.
Published by LAP LAMBERT Academic Publishing, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by LAP LAMBERT Academic Publishing Okt 2011, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The ultimate objective of brain-computer interface (BCI) is to provide humans an alternative communication channel allowing direct transmission of messages from the brain to a computer by analyzing the brain s mental activities. The BCI is usually described that a person has the ability to communicate with others without the prerequisite of brain s normal output pathways of peripheral nerves and muscles by controlling his own electroencephalographic (EEG) signals. In BCI applications, the performance and reliability of mental task analysis greatly depend on feature extraction and representation. In this book, a series of methods are proposed, including t-test-weighted time-scale plot, active segment selection, multiresolution fractal feature vector (MFFV) associated with genetic algorithm (GA), and neuro-fuzzy time-series prediction to effectively extract, select, and represent features for better classification accuracy. Compared to other well-known approaches, the experimental results show that the proposed methods are superior on both real finger movement and motor-imagery (MI) data for BCI applications. 104 pp. Englisch.
Published by LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659382434 ISBN 13: 9783659382437
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hsu Wei-YenWei-Yen Hsu received the Ph.D. degree in the Department of CSIE, National Cheng Kung University, Tainan, Taiwan, in 2008. He is an assistant professor in the Department of Information Management, National Chung Cheng Unive.
Published by LAP LAMBERT Academic Publishing, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The ultimate objective of brain-computer interface (BCI) is to provide humans an alternative communication channel allowing direct transmission of messages from the brain to a computer by analyzing the brain s mental activities. The BCI is usually described that a person has the ability to communicate with others without the prerequisite of brain s normal output pathways of peripheral nerves and muscles by controlling his own electroencephalographic (EEG) signals. In BCI applications, the performance and reliability of mental task analysis greatly depend on feature extraction and representation. In this book, a series of methods are proposed, including t-test-weighted time-scale plot, active segment selection, multiresolution fractal feature vector (MFFV) associated with genetic algorithm (GA), and neuro-fuzzy time-series prediction to effectively extract, select, and represent features for better classification accuracy. Compared to other well-known approaches, the experimental results show that the proposed methods are superior on both real finger movement and motor-imagery (MI) data for BCI applications.
Published by LAP LAMBERT Academic Publishing, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hsu Wei-YenHe received the MS and PhD degrees in the Department of Computer Science and Information Engineering from National Cheng Kung University, Tainan, Taiwan in 2001 and 2008, respectively. His current research interests includ.
Published by LAP LAMBERT Academic Publishing, 2011
ISBN 10: 384650906X ISBN 13: 9783846509067
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