首页 /研究 /A low-power, high-accuracy with fully on-chip ternary weight hardware architecture for Deep Spiking Neural Networks
LEARNING

A low-power, high-accuracy with fully on-chip ternary weight hardware architecture for Deep Spiking Neural Networks

Duy-Anh Nguyen, Xuan‐Tu Tran, Khanh N. Dang, Francesca Iacopi

发表年份
2022
引用次数
12

关键词

Computer scienceChipPower (physics)Computer hardwareEmbedded systemArchitectureArtificial neural networkSpiking neural networkTernary operationComputer architecture

相关论文

查看 LEARNING 分类全部论文