Results 281 to 290 of about 95,522 (318)

Synaptic Metaplasticity Realized in Oxide Memristive Devices

Advanced Materials, 2015
Metaplasticity, a higher order of synaptic plasticity, as well as a key issue in neuroscience, is realized with artificial synapses based on a WO3 thin film, and the activity-dependent metaplastic responses of the artificial synapses, such as spike-timing-dependent plasticity, are systematically investigated.
Zheng-Hua, Tan, Rui, Yang, Kazuya, Terabe, Xue-Bing, Yin, Xiao-Dong, Zhang, Xin, Guo   +5 more
openaire   +2 more sources

TaOx-/TiO2-Based Synaptic Devices

2017
The development of a high-density, low-power, and reliable synaptic device is essential in the implementation of highly anticipated hardware neural networks. Hence, numerous studies have investigated suitable two-terminal synaptic devices that precisely mimic biological synaptic features.
I-Ting Wang, Tuo-Hung Hou
openaire   +1 more source

Pr0.7Ca0.3MnO3 (PCMO)-Based Synaptic Devices

2017
On the basis of its operation mechanism, the RRAM can be briefly classified as filamentary type and interfacial type. Comparing to the interfacial-type RRAM, faster switching speed and higher scalability of the filamentary-type RRAM have been demonstrated for NVM applications.
Daeseok Lee, Hyunsang Hwang
openaire   +1 more source

Chalcogenide-Based Artificial Intelligence Synaptic Device

2018 14th IEEE International Conference on Solid-State and Integrated Circuit Technology (ICSICT), 2018
In this work, we investigated sputtered undoped and N-doped Sb 2 Te 3 chalcogenide phase change films by x-ray diffraction and resistance measurements. The application to artificial intelligence synaptic device is presented as well. Mean crystal size decreased from 6.8 to 2.9 nm and thus crystal growth was significantly suppressed by fine nitrides due
You Yin, Ryoya Satoh, Keita Sawao
openaire   +1 more source

Characterisation & modelling of perovskite-based synaptic memristor device

Microelectronics Reliability, 2020
Abstract Neuromorphic computing architectures are required to execute several operations such as forgetting and learning behaviours with high-speed data processing. Due to the rapid advancement in technology, various transistor-based devices like field-effect transistor (FET), complementary metal-oxide-semiconductor (CMOS), etc.
Gupta, V, Lucarelli, G, Castro-Hermosa, S, Brown, T, Ottavi, M   +4 more
openaire   +3 more sources

Electroluminescent synaptic devices with logic functions

Nano Energy, 2018
Abstract The incorporation of light into synaptic devices for neuromorphic computing with low energy consumption and high intelligence is greatly inspired by the development of optogenetics in neuroscience. However, the use of light as the outputs of synaptic devices has not been demonstrated yet, impeding the full optoelectronic integration of ...
Shuangyi Zhao, Zhenyi Ni, Hua Tan, Yue Wang, Hao Jin, Tongxin Nie, Mingsheng Xu, Xiaodong Pi, Deren Yang   +8 more
openaire   +1 more source

Artificial Funnel Nanochannel Device Emulates Synaptic Behavior

Nano Letters
Creating artificial synapses that can interact with biological neural systems is critical for developing advanced intelligent systems. However, there are still many difficulties, including device morphology and fluid selection. Based on Micro-Electro-Mechanical System technologies, we utilized two immiscible electrolytes to form a liquid/liquid ...
Peiyue Li, Junjie Liu, Jun-Hui Yuan, Yechang Guo, Shaofeng Wang, Pan Zhang, Wei Wang   +6 more
openaire   +2 more sources

Silicon-based Heterostructures for Optoelectronic Synaptic Devices

2023
Silicon (Si) is one of the most important materials for very large-scale integration (VLSI) circuits, which has achieved great success in microelectronics. The advanced mature technology and the low cost of Si have attracted interest for exploring its use in optoelectronic synaptic devices. Si-based heterostructures with rationally designed energy-band
Yue Wang, Deren Yang, Xiaodong Pi
openaire   +1 more source

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
openaire   +1 more source