Computer Science ›› 2023, Vol. 50 ›› Issue (1): 229-242.doi: 10.11896/jsjkx.220100058

• Artificial Intelligence • Previous Articles     Next Articles

Spiking Neural Network Model for Brain-like Computing and Progress of Its Learning Algorithm

HUANG Zenan, LIU Xiaojie, ZHAO Chenhui, DENG Yabin, GUO Donghui   

  1. School of Electronic Science and Engineering,Xiamen University,Xiamen,Fujian 361005,China
    IC Design R & D Engineering Center of Fujian Province,Xiamen,Fujian 361005,China
  • Received:2022-01-06 Revised:2022-08-08 Online:2023-01-15 Published:2023-01-09
  • About author:HUANG Zenan,born in 1993,Ph.D.His main research interests include artificial intelligence and neural network.
    GUO Donghui,born in 1967,Ph.D,professor.His main research interests include computer networking,artificial intelligence,optimization computing,IC design,nano device,and BioMEMS.
  • Supported by:
    Key Program of National Natural Science Foundation of China(61836010).

Abstract: With the increasingly prominent limitations of deep neural networks in practical applications,brain-like computing spiking neural networks with biological interpretability have become the focus of research.The uncertainty and complex diversity of application scenarios pose new challenges to researchers,requiring brain-like computing spiking neural networks with multi-scale architectures similar to biological brain organizations to realize the perception and decision-making function of multi-modal and uncertain information.This paper mainly introduces the multi-scale biological rational brain-like computing spiking neural network model and its learning algorithm for multi-modal information representation and uncertainty information perception,analyzing and discussing two key technical issues that the spiking neural network based on the interconnection of memristors can rea-lize multi-scale architecture brain-like computing,namely:the consistency problem of multi-modal and uncertain information with spike timing representation,and the computing fault-tolerant problem for the multi-scale spiking neural network with different learning algorithms.Finally,this paper analyzes and forecasts the further research direction of brain-like computing spiking neural network.

Key words: Brain-liked computing, Spiking neural network, Multi-scale network model, Multi-modal information, Uncertain information perception, Decision fusion, Learning algorithm, STDP

CLC Number: 

  • TP183
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