Zobrazeno 1 - 10 of 37 pro vyhledávání: '"John R. Erickson"'
1
Akademický článek
Low‐Voltage Electrochemical LixWO3 Synapses with Temporal Dynamics for Spiking Neural Networks
Autor: Qingzhou Wan, Marco Rasetto, Mohammad T. Sharbati, John R. Erickson, Sridhar Reddy Velagala, Matthew T. Reilly, Yiyang Li, Ryad Benosman, Feng Xiong
Publikováno v: Advanced Intelligent Systems, Vol 3, Iss 9, Pp n/a-n/a (2021)
Neuromorphic computing has the great potential to enable faster and more energy‐efficient computing by overcoming the von Neumann bottleneck. However, most emerging nonvolatile memory (NVM)‐based artificial synapses suffer from insufficient preci
Externí odkaz: https://doaj.org/article/3a8cbac84ba24e5693c5e042951e93d8
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2
Akademický článek
(Bi0.2Sb0.8)2Te3 based dynamic synapses with programmable spatio-temporal dynamics
Autor: Qingzhou Wan, Peng Zhang, Qiming Shao, Mohammad T. Sharbati, John R. Erickson, Kang L. Wang, Feng Xiong
Publikováno v: APL Materials, Vol 7, Iss 10, Pp 101107-101107-8 (2019)
Neuromorphic computing has recently emerged as a promising paradigm to overcome the von-Neumann bottleneck and enable orders of magnitude improvement in bandwidth and energy efficiency. However, existing complementary metal-oxide-semiconductor (CMOS)
Externí odkaz: https://doaj.org/article/519c4a18ef8548e9a9c19651a478fb89
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3
Comparing the thermal performance and endurance of resistive and PIN silicon microheaters for phase-change photonic applications
Autor: John R. Erickson, Nicholas A. Nobile, Daniel Vaz, Gouri Vinod, Carlos A. Ríos Ocampo, Yifei Zhang, Juejun Hu, Steven A. Vitale, Feng Xiong, Nathan Youngblood
Publikováno v: Optical Materials Express. 13:1677
Optical phase-change materials have enabled nonvolatile programmability in integrated photonic circuits by leveraging a reversible phase transition between amorphous and crystalline states. To control these materials in a scalable manner on-chip, hea
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2b79f7f9db997d4bc12632ad7246aa9e
https://doi.org/10.1364/ome.488564
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4
Designing fast and efficient electrically driven phase change photonics using foundry compatible waveguide-integrated microheaters
Autor: John R. Erickson, Vivswan Shah, Qingzhou Wan, Nathan Youngblood, Feng Xiong
Publikováno v: Optics express. 30(8)
Phase change chalcogenides such as Ge2Sb2Te5 (GST) have recently enabled advanced optical devices for applications such as in-memory computing, reflective displays, tunable metasurfaces, and reconfigurable photonics. However, designing phase change o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22c015723a6fa791214ba0291dcc099a
https://pubmed.ncbi.nlm.nih.gov/35472975
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7
Dynamic $(\mathrm{Bi}_{\mathrm{x}}\mathrm{Sb}_{1-\mathrm{x}})_{2}\mathrm{Te}_{\mathrm{3}}$ Synaptic Devices with Programmable Spatio-Temporal Responses
Autor: Qingzhou Wan, Kang L. Wang, Mohammad Taghi Sharbati, Peng Zhang, John R. Erickson, Feng Xiong, Qiming Shao
Publikováno v: DRC
Neuromorphic computing has emerged as a new computing paradigm to tackle the von Neumann bottleneck and enable a more energy-efficient processing of today's large-scale datasets, especially for data-intensive applications such as image and pattern re
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::194698bb8084f35ef417c2d2fd8b69b8
https://doi.org/10.1109/drc46940.2019.9046342
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8
Low‐Voltage Electrochemical Li x WO 3 Synapses with Temporal Dynamics for Spiking Neural Networks
Autor: Sridhar Reddy Velagala, Yiyang Li, Qingzhou Wan, Feng Xiong, Ryad Benosman, Mohammad Taghi Sharbati, Marco Rasetto, John R. Erickson, Matthew T. Reilly
Publikováno v: Advanced Intelligent Systems, Vol 3, Iss 9, Pp n/a-n/a (2021)
Neuromorphic computing has the great potential to enable faster and more energy‐efficient computing by overcoming the von Neumann bottleneck. However, most emerging nonvolatile memory (NVM)‐based artificial synapses suffer from insufficient preci
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13154f1344c7da869317addc64f8e829
https://doi.org/10.1002/aisy.202100021
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