Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
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Da: Basi6 International, Irving, TX, U.S.A.
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Condizione: Used. pp. 150.
Da: Majestic Books, Hounslow, Regno Unito
EUR 88,11
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 87,64
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Aggiungi al carrelloCondizione: Used. pp. 150.
Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc, 2019
ISBN 10: 0128174269 ISBN 13: 9780128174265
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 109,10
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 120,72
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Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 120,71
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 136,23
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EUR 124,43
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Aggiungi al carrelloCondizione: New. Explores machine learning techniques that have been modified and validated for the purpose of EEG signal classification using Discrete Wavelet Transform for the identification of epileptic seizures Encompasses machine learning techniques, .
Lingua: Inglese
Editore: Elsevier Science & Technology, 2019
ISBN 10: 0128174269 ISBN 13: 9780128174265
Da: preigu, Osnabrück, Germania
EUR 129,55
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. EEG Brain Signal Classification for Epileptic Seizure Disorder Detection | Sandeep Kumar Satapathy (u. a.) | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2019 | Elsevier Science & Technology | EAN 9780128174265 | Verantwortliche Person für die EU: Zeitfracht Medien GmbH, Ferdinand-Jühlke-Str. 7, 99095 Erfurt, produktsicherheit[at]zeitfracht[dot]de | Anbieter: preigu.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 88,14
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Da: Revaluation Books, Exeter, Regno Unito
EUR 97,22
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Aggiungi al carrelloPaperback. Condizione: Brand New. 150 pages. 9.00x6.00x0.40 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Elsevier Science & Technology, 2019
ISBN 10: 0128174269 ISBN 13: 9780128174265
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 150,00
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals to detect epileptic seizures using machine learning techniques. Chapters present an overview of machine learning techniques and the tools available, discuss previous studies, present empirical studies on the performance of the NN and SVM classifiers, discuss RBF neural networks trained with an improved PSO algorithm for epilepsy identification, and cover ABC algorithm optimized RBFNN for classification of EEG signal. Final chapter present future developments in the field. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need the most recent and promising automated techniques for EEG classification. Englisch.
Lingua: Inglese
Editore: Elsevier Science & Technology, 2019
ISBN 10: 0128174269 ISBN 13: 9780128174265
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 172,04
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals to detect epileptic seizures using machine learning techniques. Chapters present an overview of machine learning techniques and the tools available, discuss previous studies, present empirical studies on the performance of the NN and SVM classifiers, discuss RBF neural networks trained with an improved PSO algorithm for epilepsy identification, and cover ABC algorithm optimized RBFNN for classification of EEG signal. Final chapter present future developments in the field. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need the most recent and promising automated techniques for EEG classification.