Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Takao Marukame"'
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 11, Pp 602-610 (2023)
Lithium (Li)-ion materials such as LiCoO2 and (Li3PO4)-N (LiPON) are used in Li-ion all-solid-state batteries, and are now expected to be used as ion-electron hybrid materials to create a new degree of freedom in future integrated circuits. We fabric
Externí odkaz:
https://doaj.org/article/9ed4cdb0ffb4419da5a7a277912b1db6
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract Spike timing-dependent plasticity (STDP), which is widely studied as a fundamental synaptic update rule for neuromorphic hardware, requires precise control of continuous weights. From the viewpoint of hardware implementation, a simplified up
Externí odkaz:
https://doaj.org/article/1b42b9540ff943b4805ab44b662f914c
Autor:
Kensuke Ota, Radu Berdan, Jun Deguchi, Masumi Saitoh, Takao Marukame, Yoshifumi Nishi, Marina Yamaguchi, Shosuke Fujii
Publikováno v:
Nature Electronics. 3:259-266
Analogue in-memory computing using memristors could alleviate the performance constraints imposed by digital von Neumann systems in data-intensive tasks. Conventional linear memristors typically operate at high currents, potentially limiting power ef
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Spike timing-dependent plasticity (STDP), which is widely studied as a fundamental synaptic update rule for neuromorphic hardware, requires precise control of continuous weights. From the viewpoint of hardware implementation, a simplified update rule
Autor:
Yoshifumi Nishi, Junichi Sugino, Kumiko Nomura, Yutaka Tamura, Takao Marukame, Koichi Mizushima, Kazuo Ishikawa, Toshimitsu Kitamura, Koji Takahashi
Publikováno v:
ISCAS
An analog-to-digital mixed circuit with resistors for static neurons was implemented on a CMOS IC chip. By comparing current magnitudes via the resistors on two lines, the neuron circuit output a multiplier accumulation result and a step function at
Autor:
Takao Marukame, Koichi Mizushima, Kumiko Nomura, Junichi Sugino, Toshimitsu Kitamura, Koji Takahashi, Yutaka Tamura, Yoshifumi Nishi
Publikováno v:
Extended Abstracts of the 2020 International Conference on Solid State Devices and Materials.
Publikováno v:
Nonlinear Theory and Its Applications, IEICE. 9:466-478
Autor:
Yuichiro Mitani, Masato Motomura, Takao Marukame, Alexandre Schmid, Tetsuya Asai, Yusuke Higashi, Masamichi Suzuki, Kodai Ueyoshi
Publikováno v:
IEEE Transactions on Circuits and Systems II: Express Briefs. 64:462-466
Remarkable hardware robustness of deep learning (DL) is revealed by error injection analyses performed using a custom hardware model implementing parallelized restricted Boltzmann machines (RBMs). RBMs in deep belief networks demonstrate robustness a
Autor:
Masumi Saitoh, Shosuke Fujii, Jun Deguchi, Takao Marukame, Radu Berdan, Yoshifumi Nishi, Shoichi Kabuyanagi, Kensuke Ota
Publikováno v:
2019 Symposium on VLSI Technology.
Building compact and efficient reinforcement learning (RL) systems for mobile deployment requires departure from the von-Neumann computing architecture and embracing novel in-memory computing, and local learning paradigms. We exploit nano-scale ferro
Autor:
Yutaka Tamura, Junichi Sugino, Koji Takahashi, Yoshifumi Nishi, Takao Marukame, Toshimitsu Kitamura, Kazuo Ishikawa
Publikováno v:
ISCAS
Low power neural network hardware and its new applications have been explored to exploit its inherent advantage of artificial intelligence in comparison with humans. One such application, long-term change detection, is proposed and presented in this