Results 251 to 260 of about 84,713 (260)

ReRAM-based synaptic device for neuromorphic computing

2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014
To compete with nonvolatile FLASH memory technology, we need to develop stackable, cross-point ReRAM device. Although various materials have been reported, it is difficult to meet device criteria such as high speed operation, low power switching, switching uniformity, endurance, long-term retention and selection device for cross-point array.
Jun-Woo Jang, Sangsu Park, Yoon-Ha Jeong, Hyunsang Hwang   +3 more
openaire   +1 more source

Emerging Artificial Synaptic Devices for Neuromorphic Computing

Advanced Materials Technologies, 2019
AbstractIn today's era of big‐data, a new computing paradigm beyond today's von‐Neumann architecture is needed to process these large‐scale datasets efficiently. Inspired by the brain, which is better at complex tasks than even supercomputers with much better efficiency, the field of neuromorphic computing has recently attracted immense research ...
Qingzhou Wan, Mohammad T. Sharbati, John R. Erickson, Yanhao Du, Feng Xiong   +4 more
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Synaptic devices based on purely electronic memristors

Applied Physics Letters, 2016
Memristive devices have been widely employed to emulate biological synaptic behavior. In these cases, the memristive switching generally originates from electrical field induced ion migration or Joule heating induced phase change. In this letter, the Ti/ZnO/Pt structure was found to show memristive switching ascribed to a carrier trapping/detrapping of
Ruobing Pan, Jun Li, Fei Zhuge, Liqiang Zhu, Lingyan Liang, Hongliang Zhang, Junhua Gao, Hongtao Cao, Bing Fu, Kang Li   +9 more
openaire   +1 more source

Synaptic Devices Based on Phase-Change Memory

2017
The biological brain has the capability of learning, pattern recognition, processing imprecisely defined data, and executing complex computational tasks. Consisting of 1011 neurons and 1015 synapses as the major computational components, the biological brain is extremely power efficient, massively parallel, structurally plastic, and exceptionally ...
Yuhan Shi, Scott Fong, H.-S. Philip Wong, Duygu Kuzum   +3 more
openaire   +1 more source

Synaptic devices based on semiconductor nanocrystals

Frontiers of Information Technology & Electronic Engineering, 2022
Mingxuan Bu, Yue Wang, Lei Yin, Zhouyu Tong, Yiqiang Zhang, Deren Yang, Xiaodong Pi   +6 more
openaire   +1 more source

Synaptic devices based on HfO2 memristors

2021
M.B. González, M. Maestro-Izquierdo, S. Poblador, M. Zabala, F. Campabadal, G. González-Cordero, S. Aldana, D. Maldonado, F. Jiménez-Molinos, J.B. Roldán   +9 more
openaire   +1 more source

Organic synaptic devices for neuromorphic systems

Journal of Physics D: Applied Physics, 2018
Jia Sun, Ying Fu, Qing Wan
openaire   +1 more source

ZnO photoconductive synaptic devices for neuromorphic computing

Materials Science in Semiconductor Processing, 2023
Qiuchen Shang, Wenbo Peng, Tuo Song, Zeyang Li, Fangpei Li, Yongning He   +5 more
openaire   +1 more source

Ion-doped synaptic devices for neuromorphic applications

Macromolecular Research
Seokyoon Jang, Byeongju Kim, Yewon Park, Jiman Kim, Sang-Yun Lim, Sunghyun Lee, Jongmin Lim, Tae Joon Park, Hyunjung Lee   +8 more
openaire   +1 more source

Neuro-inspired Computing Using Resistive Synaptic Devices

2017
openaire   +1 more source