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Brain-machine interfacecircuits and systems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Brain-machine interfaceby Amir Zjajo.
Reminder of title:	circuits and systems /
Author:	Zjajo, Amir.
Published:	Cham :Springer International Publishing :2016.
Description:	xx, 163 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Brain-computer interfaces.
Online resource:	http://dx.doi.org/10.1007/978-3-319-31541-6
ISBN:	9783319315416$q(electronic bk.)

Brain-machine interfacecircuits and systems /
Zjajo, Amir.

Brain-machine interfacecircuits and systems /[electronic resource] :by Amir Zjajo. - Cham :Springer International Publishing :2016. - xx, 163 p. :ill., digital ;24 cm.

Introduction -- Neural Signal Conditioning Circuits -- Neural Signal Quantization Circuits -- Neural Signal Classification Circuits -- Brain-Machine Interface: System Optimization -- Conclusions and Recommendations -- Appendix -- Index.

This book provides a complete overview of significant design challenges in respect to circuit miniaturization and power reduction of the neural recording system, along with circuit topologies, architecture trends, and (post-silicon) circuit optimization algorithms. The introduced novel circuits for signal conditioning, quantization, and classification, as well as system configurations focus on optimized power-per-area performance, from the spatial resolution (i.e. number of channels), feasible wireless data bandwidth and information quality to the delivered power of implantable system.

ISBN: 9783319315416$q(electronic bk.)

Standard No.: 10.1007/978-3-319-31541-6doiSubjects--Topical Terms:

286641
Brain-computer interfaces.

LC Class. No.: TK7874

Dewey Class. No.: 621.3815

Brain-machine interfacecircuits and systems /
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505 0 $a Introduction -- Neural Signal Conditioning Circuits -- Neural Signal Quantization Circuits -- Neural Signal Classification Circuits -- Brain-Machine Interface: System Optimization -- Conclusions and Recommendations -- Appendix -- Index.
520 $a This book provides a complete overview of significant design challenges in respect to circuit miniaturization and power reduction of the neural recording system, along with circuit topologies, architecture trends, and (post-silicon) circuit optimization algorithms. The introduced novel circuits for signal conditioning, quantization, and classification, as well as system configurations focus on optimized power-per-area performance, from the spatial resolution (i.e. number of channels), feasible wireless data bandwidth and information quality to the delivered power of implantable system.
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