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1 Ergebnisse
1
Binarized Weight Neural-Network Inspired Ultra-Low Power Sp..:
, In:
2020 IEEE International Symposium on Circuits and Systems (ISCAS)
,
Liu, Bo
;
Cai, Hao
;
Gong, Yu
... - p. 1-5 , 2020
Link:
https://doi.org/10.1109/ISCAS45731.2020.9181172
RT T1 <cTitle>2020 IEEE International Symposium on Circuits and Systems (ISCAS)</cTitle>: T1 <Title>Binarized Weight Neural-Network Inspired Ultra-Low Power Speech Recognition Processor with Time-Domain Based Digital-Analog Mixed Approximate Computing</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9181172&Exemplar=1&LAN=DE A1 Liu, Bo A1 Cai, Hao A1 Gong, Yu A1 Zhu, Wentao A1 Li, Yan A1 Ge, Wei A1 Wang, Zhen YR 2020 SN 2158-1525 K1 Speech recognition K1 Power demand K1 MOSFET K1 Approximate computing K1 Training K1 Computer architecture K1 Time-domain analysis K1 Speech Recognition K1 Binarized Weight Neural-network K1 Approximate Computing K1 Fault-tolerant Training SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/ISCAS45731.2020.9181172 DO https://doi.org/10.1109/ISCAS45731.2020.9181172 SF ELIB - SuUB Bremen
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