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Neuromorphic Engineering: From Biological to Spike-Based Hardware Nervous Systems
Authors:Jia-Qin Yang  Ruopeng Wang  Yi Ren  Jing-Yu Mao  Zhan-Peng Wang  Ye Zhou  Su-Ting Han
Affiliation:1. College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060 P. R. China

Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060 P. R. China;2. Institute for Advanced Study, Shenzhen University, Shenzhen, 518060 P. R. China;3. Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060 P. R. China

Abstract: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.
Keywords:artificial intelligence platforms  artificial neurons and synapses  bioinspired computing  neuromorphic engineering  spiking neural networks
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