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Diversity-Based Hybrid Classifier Fusion - Rasheed, Sarbast
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Rasheed, Sarbast:

Diversity-Based Hybrid Classifier Fusion - Taschenbuch

2008, ISBN: 3836435330, Lieferbar binnen 4-6 Wochen Versandkosten:Versandkostenfrei innerhalb der BRD

ID: 9783836435338

Internationaler Buchtitel. In englischer Sprache. Verlag: VDM Verlag, Paperback, 216 Seiten, L=240mm, B=170mm, H=13mm, Gew.=418gr, [GR: 16790 - HC/Biologie/Sonstiges], Kartoniert/Broschiert, Klappentext: Electromyographic (EMG) signal analysis is the process of resolving a composite EMG signal into its constituent motor unit potential trains (classes) and it can be configured as a classification problem. An EMG signal detected by the tip of an inserted needle electrode is the superposition of the indivi­dual electrical contributions of the different motor units that are active, during a muscle contraction, and background interference. This book addresses the process of EMG signal decomposition by developing an interactive classification system, which uses multiple classifier fusion techniques in order to achieve improved classification performance. The developed system combines heterogeneous sets of base classifier ensembles of different kinds and employs both a one level classifier fusion scheme and a hybrid classifier fusion approach. Performance of the developed system was evaluated using synthetic simulated signals of known properties and real signals and compared with the performance of the constituent base classifiers. This book is directed toward graduate students and researchers in the area of electromyography and professionals in electromyography clinics. Electromyographic (EMG) signal analysis is the process of resolving a composite EMG signal into its constituent motor unit potential trains (classes) and it can be configured as a classification problem. An EMG signal detected by the tip of an inserted needle electrode is the superposition of the indivi­dual electrical contributions of the different motor units that are active, during a muscle contraction, and background interference. This book addresses the process of EMG signal decomposition by developing an interactive classification system, which uses multiple classifier fusion techniques in order to achieve improved classification performance. The developed system combines heterogeneous sets of base classifier ensembles of different kinds and employs both a one level classifier fusion scheme and a hybrid classifier fusion approach. Performance of the developed system was evaluated using synthetic simulated signals of known properties and real signals and compared with the performance of the constituent base classifiers. This book is directed toward graduate students and researchers in the area of electromyography and professionals in electromyography clinics.

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Diversity-Based Hybrid Classifier Fusion - Rasheed, Sarbast
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)

Rasheed, Sarbast:

Diversity-Based Hybrid Classifier Fusion - Taschenbuch

2008, ISBN: 3836435330, Lieferbar binnen 4-6 Wochen

ID: 9783836435338

Internationaler Buchtitel. In englischer Sprache. Verlag: VDM Verlag, Paperback, 216 Seiten, L=240mm, B=170mm, H=13mm, Gew.=418gr, [GR: 16790 - HC/Biologie/Sonstiges], Kartoniert/Broschiert, Klappentext: Electromyographic (EMG) signal analysis is the process of resolving a composite EMG signal into its constituent motor unit potential trains (classes) and it can be configured as a classification problem. An EMG signal detected by the tip of an inserted needle electrode is the superposition of the indivi­dual electrical contributions of the different motor units that are active, during a muscle contraction, and background interference. This book addresses the process of EMG signal decomposition by developing an interactive classification system, which uses multiple classifier fusion techniques in order to achieve improved classification performance. The developed system combines heterogeneous sets of base classifier ensembles of different kinds and employs both a one level classifier fusion scheme and a hybrid classifier fusion approach. Performance of the developed system was evaluated using synthetic simulated signals of known properties and real signals and compared with the performance of the constituent base classifiers. This book is directed toward graduate students and researchers in the area of electromyography and professionals in electromyography clinics.

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Diversity-Based Hybrid Classifier Fusion - Rasheed, Sarbast
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Rasheed, Sarbast:
Diversity-Based Hybrid Classifier Fusion - Taschenbuch

2008

ISBN: 9783836435338

[ED: Softcover], [PU: Vdm Verlag Dr. Müller], Electromyographic (EMG) signal analysis is the process of resolving a composite EMG signal into its constituent motor unit potential trains (classes) and it can be configuredas a classification problem. An EMG signal detected by the tip of an inserted needle electrode is the superposition of the individual electrical contributions of the different motor units that are active, during a muscle contraction, and background interference. This book addresses the process of EMG signal decomposition by developing an interactive classification system, which uses multiple classifier fusion techniques in order to achieve improved classification performance. The developed system combines heterogeneous sets of base classifier ensembles of different kinds and employs both a one level classifier fusion scheme and a hybrid classifier fusion approach. Performance of the developed system was evaluated using synthetic simulated signals of known properties and real signals and compared with the performance of the constituent base classifiers. This book is directed toward graduate students and researchers in the area of electromyography and professionals in electromyography clinics.2008. 216 p.Versandfertig in 3-5 Tagen, [SC: 0.00]

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(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Diversity-Based Hybrid Classifier Fusion - Rasheed, Sarbast
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Rasheed, Sarbast:
Diversity-Based Hybrid Classifier Fusion - Taschenbuch

2008, ISBN: 9783836435338

[ED: Softcover], [PU: Vdm Verlag Dr. Müller], Electromyographic (EMG) signal analysis is the process of resolving a composite EMG signal into its constituent motor unit potential trains (classes) and it can be configuredas a classification problem. An EMG signal detected by the tip of an inserted needle electrode is the superposition of the individual electrical contributions of the different motor units that are active, during a muscle contraction, and background interference. This book addresses the process of EMG signal decomposition by developing an interactive classification system, which uses multiple classifier fusion techniques in order to achieve improved classification performance. The developed system combines heterogeneous sets of base classifier ensembles of different kinds and employs both a one level classifier fusion scheme and a hybrid classifier fusion approach. Performance of the developed system was evaluated using synthetic simulated signals of known properties and real signals and compared with the performance of the constituent base classifiers. This book is directed toward graduate students and researchers in the area of electromyography and professionals in electromyography clinics. 2008. 216 p. Versandfertig in 3-5 Tagen

Neues Buch Booklooker.de
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Details zum Buch
Diversity-Based Hybrid Classifier Fusion
Autor:

Rasheed, Sarbast

Titel:

Diversity-Based Hybrid Classifier Fusion

ISBN-Nummer:

9783836435338

Electromyographic (EMG) signal analysis is the process of resolving a composite EMG signal into its constituent motor unit potential trains (classes) and it can be configured as a classification problem. An EMG signal detected by the tip of an inserted needle electrode is the superposition of the indivi­dual electrical contributions of the different motor units that are active, during a muscle contraction, and background interference. This book addresses the process of EMG signal decomposition by developing an interactive classification system, which uses multiple classifier fusion techniques in order to achieve improved classification performance. The developed system combines heterogeneous sets of base classifier ensembles of different kinds and employs both a one level classifier fusion scheme and a hybrid classifier fusion approach. Performance of the developed system was evaluated using synthetic simulated signals of known properties and real signals and compared with the performance of the constituent base classifiers. This book is directed toward graduate students and researchers in the area of electromyography and professionals in electromyography clinics.

Detailangaben zum Buch - Diversity-Based Hybrid Classifier Fusion


EAN (ISBN-13): 9783836435338
ISBN (ISBN-10): 3836435330
Taschenbuch
Erscheinungsjahr: 2008
Herausgeber: VDM Verlag
216 Seiten
Gewicht: 0,418 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 29.01.2009 07:42:03
Buch zuletzt gefunden am 16.01.2012 20:44:11
ISBN/EAN: 9783836435338

ISBN - alternative Schreibweisen:
3-8364-3533-0, 978-3-8364-3533-8

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