Research advance in intelligent control based on spiking neural networks
In recent years,spiking neural networks(SNN)have garnered significant attention in the fields of brain-inspired learning and intelligent control due to their advantages in energy efficiency,robustness,and the ability to incor-porate spatial-temporal information.In the field of brain-inspired learning and intelligent control,SNN architectures have shown promise in achieving complex control tasks with autonomous interaction with variations in the environment.This paper presents a comprehensive review of the development of intelligent control based on SNN and systematically sum-marizes relevant SNN control applications.Firstly,the basic concept of SNN,as well as the motivations and advantages of intelligent control based on SNN,is briefly introduced.Subsequently,the research progress of intelligent control based on SNN in recent years and its applications in fields such as robotics,unmanned vehicles,and unmanned aerial vehicles are systematically reviewed.Additionally,we summarize some hardware platforms that enable efficient implementation of SNN algorithms.Finally,the opportunities and challenges associated of SNN control are discussed.The purpose of this pa-per is to provide a technical framework for intelligent control based on SNN approach,and facilitate its rapid development and application.
spiking neural networks(SNN)deep learningneural network and intelligent controlneuromorphic com-puting
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