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Brain-Machine Interface
Details
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.
Introduces a novel, low-power analog front-end circuits for signal conditioning and quantization and digital back-end circuits for signal detection and classification in 90-nm and 65-nm CMOS technology Uses numerous examples to demonstrate procedures and system configurations for modeling, analysis and design of brain-machine interface circuits both state-of-the art software and hardware implementations Includes supplementary material: sn.pub/extras
Autorentext
Amir Zjajo received the M.Sc. and DIC degrees from the Imperial College London, London, U.K., in 2000 and the PhD. degree from Eindhoven University of Technology, Eindhoven, The Netherlands in 2010, all in electrical engineering. In 2000, he joined Philips Research Laboratories as a member of the research staff in the Mixed-Signal Circuits and Systems Group. From 2006 until 2009, he was with Corporate Research of NXP Semiconductors as a Senior Research Scientist. In 2009, he joined Delft University of Technology as a faculty member in Circuits and Systems group.
Dr. Zjajo has published more than 70 papers in referenced journals and conference proceedings, and holds more than 10 US patents or patent pending. He is the author of the books Low-Voltage High-Resolution A/D Converters: Design,Test and Calibration (Springer, 2011, Chinese translation, China Machine Press, 2015), and Stochastic Process Variations in Deep-Submicron CMOS: Circuits and Algorithms (Springer,2014). He serves as a member of Technical Program Committee of IEEE Design, Automation and Test in Europe Conference, IEEE International Symposium on Circuits and Systems, IEEE International Symposium on VLSI, IEEE International Symposium on Nanoelectronic and Information Systems, and IEEE International Conference on Embedded Computer Systems.
His research interests include power-efficient mixed-signal circuit and system design for health and mobile applications, and neuromorphic electronic circuits for autonomous cognitive systems. Dr. Zjajo won the best paper award at BIODEVICES 2015, and DATE 2012.
Inhalt
Introduction.- Neural Signal Conditioning Circuits.- Neural Signal Quantization Circuits.- Neural Signal Classification Circuits.- Brain-Machine Interface: System Optimization.- Conclusions and Recommendations.- Appendix.- Index.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783319315409
- Lesemotiv Verstehen
- Genre Electrical Engineering
- Auflage 1st edition 2016
- Sprache Englisch
- Anzahl Seiten 184
- Herausgeber Springer International Publishing
- Größe H241mm x B160mm x T16mm
- Jahr 2016
- EAN 9783319315409
- Format Fester Einband
- ISBN 3319315404
- Veröffentlichung 08.04.2016
- Titel Brain-Machine Interface
- Autor Amir Zjajo
- Untertitel Circuits and Systems
- Gewicht 448g