SPIKING

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A chaotic spiking backpropagation approach to brain learning
《National Science Review》2024年第6期76-77,共2页Guanrong Chen 
Spiking neural networks(SNNs)[1]are known for their superior energy efficiency,achieved through spiking signal transmission that mirrors biological nervous systems,thus solving the unsustainable energy-consumption pro...
关键词：NETWORKS NEURAL CHAOTIC 
Brain-inspired chaotic spiking backpropagation
《National Science Review》2024年第6期162-172,共11页Zijian Wang Peng Tao Luonan Chen 
supported by the National Natural Science Foundation of China(T2350003,T2341007,12131020 and 31930022);the Special Fund for Science and Technology Innovation Strategy of Guangdong Province(2021B0909050004 and 2021B0909060002);the National Key R&D Program of China(2022YFA1004800);the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB38040400);JST MoonshotR&D(JPMJMS2021).
Spiking neural networks (SNNs) have superior energy efficiency due to their spiking signal transmission,which mimics biological nervous systems, but they are difficult to train effectively. Although surrogategradient-...
关键词：spiking neural networks surrogate gradient local minima backpropagation brain-inspired learning CHAOS 
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