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Brain-Machine Interface Engineering
Record Type:
Electronic resources : Monograph/item
Title/Author:
Brain-Machine Interface Engineering/ by Justin C. Sanchez, José C. Príncipe.
Author:
Sanchez, Justin C.
other author:
Príncipe, José C.
Description:
X, 234 p.online resource. :
Contained By:
Springer Nature eBook
Subject:
Engineering. -
Online resource:
Fulltext (查閱電子書全文)
ISBN:
9783031016219
Brain-Machine Interface Engineering
Sanchez, Justin C.
Brain-Machine Interface Engineering
[electronic resource] /by Justin C. Sanchez, José C. Príncipe. - 1st ed. 2007. - X, 234 p.online resource. - Synthesis Lectures on Biomedical Engineering,1930-0336. - Synthesis Lectures on Biomedical Engineering,.
Contents: Introduction to Neural Interfaces -- Foundations of Neuronal Representations -- Input-Outpur BMI Models -- Regularization Techniques for BMI Models -- Neural Decoding Using Generative BMI Models -- Adaptive Algorithms for Point Processes -- BMI Systems.
Neural interfaces are one of the most exciting emerging technologies to impact bioengineering and neuroscience because they enable an alternate communication channel linking directly the nervous system with man-made devices. This book reveals the essential engineering principles and signal processing tools for deriving control commands from bioelectric signals in large ensembles of neurons. The topics featured include analysis techniques for determining neural representation, modeling in motor systems, computing with neural spikes, and hardware implementation of neural interfaces. Beginning with an exploration of the historical developments that have led to the decoding of information from neural interfaces, this book compares the theory and performance of new neural engineering approaches for BMIs. Contents: Introduction to Neural Interfaces / Foundations of Neuronal Representations / Input-Outpur BMI Models / Regularization Techniques for BMI Models / Neural Decoding Using Generative BMI Models / Adaptive Algorithms for Point Processes / BMI Systems.
ISBN: 9783031016219
Standard No.: 10.1007/978-3-031-01621-9doiSubjects--Topical Terms:
423497
Engineering.
LC Class. No.: T1-995
Dewey Class. No.: 620
Brain-Machine Interface Engineering
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Neural interfaces are one of the most exciting emerging technologies to impact bioengineering and neuroscience because they enable an alternate communication channel linking directly the nervous system with man-made devices. This book reveals the essential engineering principles and signal processing tools for deriving control commands from bioelectric signals in large ensembles of neurons. The topics featured include analysis techniques for determining neural representation, modeling in motor systems, computing with neural spikes, and hardware implementation of neural interfaces. Beginning with an exploration of the historical developments that have led to the decoding of information from neural interfaces, this book compares the theory and performance of new neural engineering approaches for BMIs. Contents: Introduction to Neural Interfaces / Foundations of Neuronal Representations / Input-Outpur BMI Models / Regularization Techniques for BMI Models / Neural Decoding Using Generative BMI Models / Adaptive Algorithms for Point Processes / BMI Systems.
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Synthesis Collection of Technology (R0) (SpringerNature-85007)
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