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神经形态工程:从生物到基于尖峰的硬件神经系统。

Neuromorphic Engineering: From Biological to Spike-Based Hardware Nervous Systems.

机构信息

College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China.

Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China.

出版信息

Adv Mater. 2020 Dec;32(52):e2003610. doi: 10.1002/adma.202003610. Epub 2020 Nov 9.

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.

摘要

人类大脑是一种复杂的、高性能的生物计算机,能够高效、低功耗地并行处理多个复杂任务。科学家们长期以来一直追求能够与人类大脑相媲美的人工智能 (AI)。基于神经形态计算平台的尖峰神经网络模拟了智能大脑的结构和信息处理方式,为构建人工智能提供了新的思路。材料工程、器件物理、芯片集成和神经科学的快速发展,使得神经形态计算取得了令人兴奋的进展,目标是克服冯·诺依曼瓶颈。本文回顾了生物神经系统中神经元和突触的结构和工作原理的相关基础知识。然后概述了从人工突触和神经元到基于尖峰的神经形态计算平台的神经形态硬件系统的发展。希望本文的综述能为类脑计算的发展带来新的启示。

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