Details

Autor(en) / Beteiligte

• Yang, Jia‐Qin
• Wang, Ruopeng
• Ren, Yi
• Mao, Jing‐Yu
• Wang, Zhan‐Peng
• Zhou, Ye
• Han, Su‐Ting

Titel

Neuromorphic Engineering: From Biological to Spike‐Based Hardware Nervous Systems

Ist Teil von

• Advanced materials (Weinheim), 2020-12, Vol.32 (52), p.e2003610-n/a

Ort / Verlag

Germany: Wiley Subscription Services, Inc

Erscheinungsjahr

2020

Quelle

Wiley-Blackwell Journals

Beschreibungen/Notizen

• 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. Spiking neural networks based on neuromorphic computing platforms simulate the architecture and information processing of the brain, providing a new insight for building machines having artificial intelligence. A comprehensive overview of the development of neuromorphic engineering from biological nervous systems to spike‐based neuromorphic computing platforms is provided.