DeepTempo: A Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks
文献类型：期刊论文
| 作者 | Shi, Cong; Wang, Tengxiao; He, Junxian; Zhang, Jianghao; Liu, Liyuan; Wu, Nanjian |
| 刊名 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
 |
| 出版日期 | 2021 |
| 卷号 | 68期号:5页码:1581-1585 |
| 源URL | [http://ir.semi.ac.cn/handle/172111/31231]  |
| 专题 | 半导体研究所_半导体超晶格国家重点实验室 |
| 推荐引用方式 GB/T 7714 | Shi, Cong; Wang, Tengxiao; He, Junxian; Zhang, Jianghao; Liu, Liyuan; Wu, Nanjian. DeepTempo: A Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS,2021,68(5):1581-1585. |
| APA | Shi, Cong; Wang, Tengxiao; He, Junxian; Zhang, Jianghao; Liu, Liyuan; Wu, Nanjian.(2021).DeepTempo: A Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS,68(5),1581-1585. |
| MLA | Shi, Cong; Wang, Tengxiao; He, Junxian; Zhang, Jianghao; Liu, Liyuan; Wu, Nanjian."DeepTempo: A Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 68.5(2021):1581-1585. |
入库方式： OAI收割
来源：半导体研究所
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