Neuromorphic Engineering: From Biological to Spike‐Based Hardware Nervous Systems
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- Jia‐Qin Yang
- College of Electronics and Information Engineering Shenzhen University Shenzhen 518060 P. R. China
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- Ruopeng Wang
- College of Electronics and Information Engineering Shenzhen University Shenzhen 518060 P. R. China
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- Yi Ren
- Institute for Advanced Study Shenzhen University Shenzhen 518060 P. R. China
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- Jing‐Yu Mao
- Institute for Advanced Study Shenzhen University Shenzhen 518060 P. R. China
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- Zhan‐Peng Wang
- Institute for Advanced Study Shenzhen University Shenzhen 518060 P. R. China
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- Ye Zhou
- Institute for Advanced Study Shenzhen University Shenzhen 518060 P. R. China
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- Su‐Ting Han
- Institute of Microscale Optoelectronics Shenzhen University Shenzhen 518060 P. R. China
抄録
<jats:title>Abstract</jats:title><jats:p>The human brain is a sophisticated, high‐performance biocomputer that processes multiple complex tasks in parallel with high efficiency and remarkably low power consumption. Scientists have long been pursuing an artificial intelligence (AI) that can rival the human brain. Spiking neural networks based on neuromorphic computing platforms simulate the architecture and information processing of the intelligent brain, providing new insights for building AIs. The rapid development of materials engineering, device physics, chip integration, and neuroscience has led to exciting progress in neuromorphic computing with the goal of overcoming the von Neumann bottleneck. Herein, fundamental knowledge related to the structures and working principles of neurons and synapses of the biological nervous system is reviewed. An overview is then provided on the development of neuromorphic hardware systems, from artificial synapses and neurons to spike‐based neuromorphic computing platforms. It is hoped that this review will shed new light on the evolution of brain‐like computing.</jats:p>
収録刊行物
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- Advanced Materials
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Advanced Materials 32 (52), 2020-11-09
Wiley