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.

Qing Wan, PhD, is Professor in the School of Electronic Science and Engineering at Nanjing University in China. He received his doctorate from the Shanghai Institute of Micro-System and Information Technology, Chinese Academy of Sciences in 2004.

Yi Shi, PhD, is Full Professor in the School of Electronic Engineering at Nanjing University. He received his doctorate from the Department of Physics at Nanjing University in 1989.