Details

Neuromorphic Devices for Brain-inspired Computing


Neuromorphic Devices for Brain-inspired Computing

Artificial Intelligence, Perception, and Robotics
1. Aufl.

von: Qing Wan, Yi Shi

124,99 €

Verlag: Wiley-VCH
Format: EPUB
Veröffentl.: 10.12.2021
ISBN/EAN: 9783527835300
Sprache: englisch
Anzahl Seiten: 256

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Beschreibungen

<p><B>Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence</b></p> <p>In <i>Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics,</i> 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. <p>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: <ul><li>A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms</li> <li>Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors <li>Practical discussions of neuromorphic devices based on chalcogenide and organic materials</li> <li>In-depth examinations of neuromorphic computing and perceptual systems with emerging devices</li></ul> <p>Perfect for materials scientists, biochemists, and electronics engineers, <i>Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics</i> will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.
1: Two-terminal Neuromorphic Memristors<br> 2: Spintronic Neuromorphic Devices<br> 3: Multi-terminal Neuromorphic Devices with Cognitive Behaviors<br> 4: Neuromorphic Devices based on Chalcogenide materials<br> 5: Neuromorphic Devices Based on Organic materials<br> 6: Neuromorphic Computing Systems with Emerging Devices<br> 7: Neuromorphic perceptual Systems with Emerging Devices<br>
<p><b><i>Qing Wan, PhD,</b> 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.</i></p> <p><b><i>Yi Shi, PhD, </b>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.</i>
<p><B>Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence</b></p> <p>In <i>Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics,</i> 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. <p>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: <ul><li>A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms</li> <li>Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors <li>Practical discussions of neuromorphic devices based on chalcogenide and organic materials</li> <li>In-depth examinations of neuromorphic computing and perceptual systems with emerging devices</li></ul> <p>Perfect for materials scientists, biochemists, and electronics engineers, <i>Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics</i> will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.

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