SPIKING

作品数：66被引量：93H指数：4
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SpikingMiniLM:energy-efficient spiking transformer for natural language understanding
《Science China(Information Sciences)》2024年第10期111-124,共14页Jiayu ZHANG Jiangrong SHEN Zeke WANG Qinghai GUO Rui YAN Gang PAN Huajin TANG 
supported by National Natural Science Foundation of China(Grant Nos.62236007,62306274,61925603);Huawei and Zhejiang University Brain-Inspired Computing Joint Innovation Research Project(Grant No.FA2019111021-2023-01)。
In the era of large-scale pretrained models,artificial neural networks(ANNs)have excelled in natural language understanding(NLU)tasks.However,their success often necessitates substantial computational resources and en...
关键词：spiking neural networks natural language understanding spiking Transformer spike-based attention multi-step encoding ANN-to-SNN distillation 
Deterministic conversion rule for CNNs to efficient spiking convolutional neural networks被引量：2
《Science China(Information Sciences)》2020年第2期196-214,共19页Xu YANG Zhongxing ZHANG Wenping ZHU Shuangming YU Liyuan LIU Nanjian WU 
supported by National Natural Science Foundation of China(Grant Nos.61704167,61434004);Beijing Municipal Science and Technology Project(Grant No.Z181100008918009);Youth Innovation Promotion Association Program,Chinese Academy of Sciences(Grant No.2016107);Strategic Priority Research Program of Chinese Academy of Science(Grant No.XDB32050200).
This paper proposes a general conversion theory to reveal the relations between convolutional neural network(CNN)and spiking convolutional neural network(spiking CNN)from structure to information processing.Based on t...
关键词：convolutional NEURAL networks(CNN) SPIKING NEURAL networks(SNN) image classification CONVERSION RULE noise robustness neuromorphic hardware 
Area-efficient memristor spiking neural networks and supervised learning method被引量：1
《Science China(Information Sciences)》2019年第9期196-198,共3页Errui ZHOU Liang FANG Rulin LIU Zhensen TANG 
supported by National Natural Science Foundation of China (Grant Nos. 61332003, 61832007)
Dear editor,Memristors have attracted a lot of attention since HP Labs first reported their memristive devices[1].They have been employed in many fields,including non-volatile memory,image processing,and neuromorphic ...
关键词：simulation Area-efficient MEMRISTOR SPIKING NEURAL NETWORKS and supervised LEARNING method 
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