Neuromorphic Devices for Brain-inspired Computing: Artificial Intelligence, Perception and Robotics - Hardcover

Über die Autorin bzw. den Autor

Qing Wan is currently a professor in the School of Electronic Science and Engineering, Nanjing University, China. He received PhD degree from Shanghai Institute of micro-system and Information Technology, Chinese Academy of Sciences in 2004. From 2004 to 2005, he worked as a postdoctoral researcher at the Department of Materials, University of Cambridge. From 2006 to 2007, he also worked as a postdoctoral researcher at the Department of Electronic Engineering, University of Michigan, Ann Arbor. His research focused on the semiconductor micro/nano structures for new-concept device applications. Qing Wan has published more than 200 scientific papers and SCI cited more than 10000 times. Qing Wan has won many awards, including National Youth Top-notch Talent, China Youth Science and Technology Award, Natural Science prize of the Ministry of Education (first-class prize), Author of National Excellent Doctoral Dissertation of PR China, Special award of the President of the Chinese Academy of Sciences, NSF distinguished Young Scholars.
 
Yi Shi is a full professor of the school of Electronic Engineering, Nanjing University. He obtained Ph. D in Department of physics, Nanjing University in 1989. He has been visiting professor to Cambridge University, Tohoku University, and University of California (Berkeley). He has published over 300 articles on peer reviewed journals including Nature Commun., Nano Lett., Adv. Mater., and Appl. Phys. Lett. He was promoted to Changjiang Chair Professor in 2007, and is the principle scientist of several scientific research plans, such as the national basic research program of China. His research interests mainly focused on Nanoelectronics and Nanophotoelectronics.

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Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence

In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications.

Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes:

• A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms
• Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors
• Practical discussions of neuromorphic devices based on chalcogenide and organic materials
• In-depth examinations of neuromorphic computing and perceptual systems with emerging devices

Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.