脉冲神经网络研究现状与应用进展
A Review of Recent Advances and Application for Spiking Neural Networks
摘要
Abstract
Spiking neural network(SNN)is a new generation of artificial neural network.It is more biologically plausible and has been widely concerned by scholars owing to its unique information coding schemes,rich spatiotemporal dynamics,and event-driven operating mode with low power.In recent years,SNN has been explored and applied in many fields such as medical health,industrial detection,and intelligent driving.First,the basic elements and learning algorithms of SNN are introduced,including classical spiking neuron models,spike-timing dependent plasticity(STDP),and common information coding methods.The advantages and disadvantages of the learning algorithms are also analyzed.Then,the mainstream software simulators and neuromorphic hardware of SNN are summarized.Subsequently,the research progress and application scenarios of SNN in terms of computer vision,natural language processing,and reasoning decision are introduced.Particularly,SNN has shown strong potentials in tasks such as object detection,action recognition,semantic cognition,and speech recognition,significantly improving computational performance.Future research and application of SNN should focus on strengthening the research on key core technologies,promoting the application of technological achievements,and continuously optimizing the industrial ecology,thus to catch up with the advanced international level.Moreover,continuous research and breakthroughs of brain-inspired systems and control theories will promote the establishment of large-scale SNN models and are expected to broaden the application prospect of artificial intelligence.关键词
脉冲神经网络/类脑计算/学习算法/神经形态芯片/应用场景Key words
spiking neural network/brain-inspired computing/learning algorithm/neuromorphic chip/application scenario分类
信息技术与安全科学引用本文复制引用
刘浩,柴洪峰,孙权,云昕,李鑫..脉冲神经网络研究现状与应用进展[J].中国工程科学,2023,25(6):61-79,19.基金项目
国家重点研发计划项目(2021YFC3300600) （2021YFC3300600）
中国工程院咨询项目"数字化转型背景下金融风险监测与预警体系战略研究"(2023-XY-43) （2023-XY-43）
国家自然科学基金项目(72201161) （72201161）
长三角科技创新共同体联合攻关项目(2022CSJGG0800,2021-YF09-00114-GX,PO3522083587,PO3522083675,HP2300490) National Key R&D Program of China(2021YFC3300600) （2022CSJGG0800,2021-YF09-00114-GX,PO3522083587,PO3522083675,HP2300490）
Chinese Academy of Engineering project"Strategic Research on Financial Risk Monitoring and Early Warning System under the Background of Digital Transformation"(2023-XY-43) （2023-XY-43）
National Natural Science Fund project(72201161) （72201161）
Joint Research Project of Yangtze River Delta Community of Sci-tech Innovation(2022CSJGG0800,2021-YF09-00114-GX,PO3522083587,PO3522083675,HP2300490) （2022CSJGG0800,2021-YF09-00114-GX,PO3522083587,PO3522083675,HP2300490）
