Results 1 to 10 of about 14,242 (162)

Room-temperature valley transistors for low-power neuromorphic computing [PDF]

Nature Communications, 2022
Valleytronic devices employ the electronic valley degree of freedom to realize potential low-power electronic applications. Here, the authors utilize a topological semiconductor to engineer valley polarization transistors with long lifetimes and ...
Jiewei Chen, Yue Zhou, Jianmin Yan, Jidong Liu, Lin Xu, Jingli Wang, Tianqing Wan, Yuhui He, Wenjing Zhang, Yang Chai   +9 more
doaj   +5 more sources

Nanofiber Channel Organic Electrochemical Transistors for Low‐Power Neuromorphic Computing and Wide‐Bandwidth Sensing Platforms [PDF]

Advanced Science, 2021
Organic neuromorphic computing/sensing platforms are a promising concept for local monitoring and processing of biological signals in real time. Neuromorphic devices and sensors with low conductance for low power consumption and high conductance for low ...
Sol‐Kyu Lee, Young Woon Cho, Jong‐Sung Lee, Young‐Ran Jung, Seung‐Hyun Oh, Jeong‐Yun Sun, SangBum Kim, Young‐Chang Joo   +7 more
doaj   +5 more sources

Low‐Power Computing with Neuromorphic Engineering [PDF]

Advanced Intelligent Systems, 2021
The increasing power consumption in the existing computation architecture presents grand challenges for the performance and reliability of very‐large‐scale integrated circuits. Inspired by the characteristics of the human brain for processing complicated
Dingbang Liu, Hao Yu, Yang Chai
doaj   +3 more sources

WO_x channel engineering of Cu-ion-driven synaptic transistor array for low-power neuromorphic computing. [PDF]

Sci Rep, 2023
AbstractThe multilevel current states of synaptic devices in artificial neural networks enable next-generation computing to perform cognitive functions in an energy-efficient manner. Moreover, considering large-scale synaptic arrays, multiple states programmed in a low-current regime may be required to achieve low energy consumption, as demonstrated by
Jeon S, Kang H, Kwak H, Noh K, Kim S, Kim N, Kim HW, Hong E, Kim S, Woo J.   +9 more
europepmc   +4 more sources

Reconfigurable In-Sensor Computing Memristor for Olfactory SNN and Reservoir Hybrid Neuromorphic Computing [PDF]

Research
Traditional gas sensing systems are facing efficiency challenges due to physically separated von Neumann architectures, making the construction of in-sensor computing neuromorphic olfactory systems urgently needed for low-power and low-latency scenarios.
Lin Lu, Jinhao Zhang, Qingxin Chen, Jialin Meng, Yongjin Zou, Yilin Wang, Tianyu Wang   +6 more
doaj   +2 more sources

Low-Power Memristor for Neuromorphic Computing: From Materials to Applications

Nano-Micro Letters
As an emerging memory device, memristor shows great potential in neuromorphic computing applications due to its advantage of low power consumption. This review paper focuses on the application of low-power-based memristors in various aspects. The concept
Zhipeng Xia, Xiao Sun, Zhenlong Wang, Jialin Meng, Boyan Jin, Tianyu Wang   +5 more
doaj   +3 more sources

Synaptic Plasticity Engineering for Neural Precision, Temporal Learning, and Scalable Neuromorphic Systems [PDF]

Nano-Micro Letters
Highlights This review provides an in-depth discussion of computing-unit optimization through synaptic plasticity engineering, enabling precise weight modulation in spatial models and effective temporal information processing in dynamic neural networks ...
Zhengjun Liu, Yuxiao Fang, Qing Liu, Bobo Tian, Chun Zhao   +4 more
doaj   +2 more sources

Ultra-low power carbon nanotube/porphyrin synaptic arrays for persistent photoconductivity and neuromorphic computing

Nature Communications
Developing devices with a wide-temperature range persistent photoconductivity (PPC) and ultra-low power consumption remains a significant challenge for optical synaptic devices used in neuromorphic computing. By harnessing the PPC properties in materials,
Jian Yao, Qinan Wang, Yong Zhang, Yu Teng, Jing Li, Pin Zhao, Chun Zhao, Ziyi Hu, Zongjie Shen, Liwei Liu, Dan Tian, Song Qiu, Zhongrui Wang, Lixing Kang, Qingwen Li   +14 more
doaj   +3 more sources

Adaptive Extreme Edge Computing for Wearable Devices

Frontiers in Neuroscience, 2021
Wearable devices are a fast-growing technology with impact on personal healthcare for both society and economy. Due to the widespread of sensors in pervasive and distributed networks, power consumption, processing speed, and system adaptation are vital ...
Erika Covi, Elisa Donati, Xiangpeng Liang, David Kappel, Hadi Heidari, Melika Payvand, Wei Wang   +6 more
doaj   +1 more source

CMOS-compatible neuromorphic devices for neuromorphic perception and computing: a review

International Journal of Extreme Manufacturing, 2023
Neuromorphic computing is a brain-inspired computing paradigm that aims to construct efficient, low-power, and adaptive computing systems by emulating the information processing mechanisms of biological neural systems.
Yixin Zhu, Huiwu Mao, Ying Zhu, Xiangjing Wang, Chuanyu Fu, Shuo Ke, Changjin Wan, Qing Wan   +7 more
doaj   +1 more source