Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Hiroshi Fuketa"'
Publikováno v:
IEEE Access, Vol 12, Pp 102470-102480 (2024)
In this paper, a table lookup-based computing technique is proposed to perform convolutional neural network (CNN) inference without multiplication, and its FPGA implementation is demonstrated as a proof-of-concept. Conventionally, the hardware specif
Externí odkaz:
https://doaj.org/article/371fea10c1b349e0a72e1c6fa63a5d10
Autor:
Takumi Inaba, Hiroshi Oka, Hidehiro Asai, Hiroshi Fuketa, Shota Iizuka, Kimihiko Kato, Shunsuke Shitakata, Koichi Fukuda, Takahiro Mori
Publikováno v:
IEEE Access, Vol 12, Pp 12458-12464 (2024)
This study investigated changes in low-frequency noise sources associated with short-channel bulk metal-oxide-semiconductor field-effect transistors (MOSFETs) by analyzing random telegraph noise (RTN) from 300 K down to 3 K. The power spectral densit
Externí odkaz:
https://doaj.org/article/86a0341b30734716b05676159ca3cc5b
Autor:
Hiroshi Oka, Takumi Inaba, Shunsuke Shitakata, Kimihiko Kato, Shota Iizuka, Hidehiro Asai, Hiroshi Fuketa, Takahiro Mori
Publikováno v:
IEEE Access, Vol 11, Pp 121567-121573 (2023)
This study investigates the origin of low-frequency (LF) 1/ $f$ noise in Si n-channel metal-oxide-semiconductor field-effect transistors (n-MOSFETs) under cryogenic operation. The fluctuation of the drain current increased with decreasing temperature
Externí odkaz:
https://doaj.org/article/85ccaad116e34e26a41e0f4a9d4dbb21
Autor:
Takumi Inaba, Yusuke Chiashi, Minoru Ogura, Hidehiro Asai, Hiroshi Fuketa, Hiroshi Oka, Shota Iizuka, Kimihiko Kato, Shunsuke Shitakata, Takahiro Mori
Publikováno v:
Applied Physics Express, Vol 17, Iss 7, p 074002 (2024)
Transfer learning was examined to predict current-voltage (I-V) characteristics of MOSFETs at cryogenic temperatures. An experimental dataset was obtained from approximately 800 silicon-on-insulator MOSFETs using an automated cryogenic wafer prober t
Externí odkaz:
https://doaj.org/article/0dec5a0c307843deb506f838df9417f0
Autor:
Hiroshi Fuketa
Publikováno v:
Sensors, Vol 21, Iss 24, p 8268 (2021)
This paper presents an ultra-low power hand gesture sensor using electrostatic induction for mobile devices. Two electrodes, which consist of electret foils stacked on metal sheets, are used to recognize two gestures such as hand movements from left
Externí odkaz:
https://doaj.org/article/4635ce8a910d4d28a338f599737a8e8a
Autor:
Makoto Kubo, Ryotaro Eda, Shotaro Maehana, Hiroshi Fuketa, Norihiro Shinkai, Naohisa Kawamura, Hidero Kitasato, Hideaki Hanaki
Publikováno v:
Journal of Water & Health; Mar2024, Vol. 22 Issue 3, p601-611, 11p
Autor:
Hiroshi Fuketa
Publikováno v:
IEEJ Transactions on Fundamentals and Materials. 142:169-174
Autor:
Hiroshi Fuketa
Publikováno v:
IEEE Transactions on Circuits and Systems II: Express Briefs. 69:334-338
In this brief, we propose an audio feature extractor, based on a time delay neural network (TDNN), for ultra-low power keyword spotting (KWS). Conventionally, mel-frequency cepstrum coefficients (MFCCs) are widely used as features for KWS. However, a
Autor:
Hiroshi Fuketa
Publikováno v:
IEEE Solid-State Circuits Letters. 5:82-85
Publikováno v:
2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits).