Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods.
Dullal Ghosh holds a bachelor's degree in Mechanical Engineering from NIT-Allahabad, India. He has completed master's program in Mechatronics from KTH, Sweden and master thesis work related to Brain-Computer Interface at TU Munich, Germany as an Erasmus exchange scholar in the year 2012. Currently he works as a Design Engineer at General Electric.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods. 68 pp. Englisch. N° de réf. du vendeur 9783659454721
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ghosh DullalDullal Ghosh holds a bachelor s degree in Mechanical Engineering from NIT-Allahabad, India. He has completed master s program in Mechatronics from KTH, Sweden and master thesis work related to Brain-Computer Interface at . N° de réf. du vendeur 5157135
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch. N° de réf. du vendeur 9783659454721
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods. N° de réf. du vendeur 9783659454721
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Commanding An Avatar Through Mind | An Approach Towards a Paradigm Shift in Adaptive Brain-Computer Interface for Robotic or Wheel-Chair Based Navigation | Dullal Ghosh (u. a.) | Taschenbuch | 68 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659454721 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 105590652
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Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Paperback. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA77336594547296
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