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类脑计算研究进展 被引量:3

Research Progress in Brain-Inspired Computing
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摘要 类脑计算是国际上的热门研究领域,也是人工智能发展的重要转折点。首先,回顾了近年来研究学者对局部脑功能运行机理的重要发现,并了解了其在类脑模型中的应用,如注意力机制和类脑导航等。随后阐述了神经形态计算芯片和人工神经元等类脑计算硬件的结构和特点,并对各国研究进展进行了简要梳理,从多个角度对类脑计算的研究内容、研究目标、研究方案和技术路线进行了全面总结。最后结合各国脑研究计划,分别从硬件和模型两个层面对芯片-算法兼容性及局部-全局整合等类脑计算的研究趋势进行了展望。 Brain-inspired computing is an international hot research field,as well as an important turning point in the development of artificial intelligence.Firstly,we review the important discovery and comprehension of local brain function running mechanism and its application in brain-inspired model,such as attention mechanism,brain-inspired navigation.Then the structure and characteristics of brain-inspired computing hardware such as neuromorphic computing chip and artificial neuron are expounded.And the research progress of various countries is summarized briefly.Comprehensive summarization of the research contents,research objectives,research schemes and technical routes of brain-inspired computing is performed from multiple perspectives.Finally the research trends of brain-inspired computing,such as chip-algorithm compatibility and local-global integration,from two aspects of hardware and model in combination with brain-inspired research plans of various countries are prospected.
作者 莫宏伟 丛垚 MO Hong-wei;CONG Yao(College of Intelligent Systems Science and Engineering, Harbin Engineering University,Harbin 150001,China)
出处 《导航定位与授时》 CSCD 2021年第4期53-67,共15页 Navigation Positioning and Timing
基金 中央高校基础科研业务费(3072020CFT0402)。
关键词 人工智能 类脑计算 类脑模型 类脑导航 神经形态计算芯片 Artificial intelligence Brain-inspired computing Brain-inspired model Brain-inspired navigation Neuromorphic computing chip
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  • 1Furber S B, Galluppi F, Temple S, et al. The spinnaker project. Proc IEEE, 2014, 102: 652-665.
  • 2Beyeler M, Carlson K D, Chou T S, et al. CARLsim 3: a user-friendly and highly optimized library for the creation of neurobiologically detailed spiking neural networks. In: Proceedings of International Joint Conference on Neural Networks (IJCNN), Killarney, 2015. 1-8.
  • 3Merolla P A, Arthur J V, Alvarez-Icaza R, et al. A million spiking-neuron integrated circuit with a scalable commu- nication network and interface. Science, 2014, 345: 668-673.
  • 4Qiao N, Mostafa H, Corradi F, et al. A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128 K synapses. Front Neurosci, 2015, 9: 141.
  • 5Dayan P, Abbott L F. Theoretical Neuroscience. Cambridge: MIT Press, 2001. 11-52.
  • 6Neil D, Liu S C. Minitaur, an event-driven FPGA-based spiking network accelerator. IEEE Trans Very Large Scale Integr Syst, 2014, 22: 2621-2628.
  • 7Chang-Lin Li,Kai-Cheng Li,Dan Wu,Yan Chen,Hao Luo,Jing-Rong Zhao,Sa-Shuang Wang,Ming-Ming Sun,Ying-Jin Lu,Yan-Qing Zhong,Xu-Ye Hu,Rui Hou,Bei-Bei Zhou,Lan Bao,Hua-Sheng Xiao,Xu Zhang.Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity[J].Cell Research,2016,26(1):83-102. 被引量:24

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