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类脑计算综述:架构、应用及未来趋势。

An overview of brain-like computing: Architecture, applications, and future trends.

作者信息

Ou Wei, Xiao Shitao, Zhu Chengyu, Han Wenbao, Zhang Qionglu

机构信息

The School of Cyberspace Security, Hainan University, Hainan, China.

Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China.

出版信息

Front Neurorobot. 2022 Nov 24;16:1041108. doi: 10.3389/fnbot.2022.1041108. eCollection 2022.

Abstract

With the development of technology, Moore's law will come to an end, and scientists are trying to find a new way out in brain-like computing. But we still know very little about how the brain works. At the present stage of research, brain-like models are all structured to mimic the brain in order to achieve some of the brain's functions, and then continue to improve the theories and models. This article summarizes the important progress and status of brain-like computing, summarizes the generally accepted and feasible brain-like computing models, introduces, analyzes, and compares the more mature brain-like computing chips, outlines the attempts and challenges of brain-like computing applications at this stage, and looks forward to the future development of brain-like computing. It is hoped that the summarized results will help relevant researchers and practitioners to quickly grasp the research progress in the field of brain-like computing and acquire the application methods and related knowledge in this field.

摘要

随着技术的发展,摩尔定律即将走到尽头,科学家们正在尝试在类脑计算中寻找新的出路。但我们对大脑的工作方式仍然知之甚少。在现阶段的研究中,类脑模型都是为了模仿大脑结构以实现大脑的某些功能而构建的,然后不断完善理论和模型。本文总结了类脑计算的重要进展和现状,归纳了普遍认可且可行的类脑计算模型,介绍、分析并比较了较为成熟的类脑计算芯片,概述了现阶段类脑计算应用的尝试与挑战,并展望了类脑计算的未来发展。希望总结的成果能帮助相关研究人员和从业者快速掌握类脑计算领域的研究进展,并获取该领域的应用方法及相关知识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdd4/9730831/1bab1f288286/fnbot-16-1041108-g0001.jpg

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