Results 231 to 240 of about 76,792 (271)

Piezotronic Graphene Artificial Sensory Synapse

Advanced Functional Materials, 2019
AbstractThe human somatosensory system, consisting of receptors, transmitters, and synapses, functions as the medium for external mechanical stimuli perception and sensing signal delivery/processing. Developing sophisticated artificial sensory synapses with a high performance, uncomplicated fabrication process, and low power consumption is still a ...
Youhui Chen, Guoyun Gao, Jing Zhao, Huai Zhang, Jinran Yu, Xixi Yang, Qian Zhang, Wenliang Zhang, Shuya Xu, Jia Sun, Yanfang Meng, Qijun Sun   +11 more
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Neuromorphic Synapses for Artificial Dendrites

Analog Integrated Circuits and Signal Processing, 1997
We describe neuromorphic, variable-weight synapses on artificial dendrites that facilitate experimentation with correlative adaptation rules. Attention is focused on those aspects of biological synaptic function that could affect a neuromorphic network‘s computational power and adaptive capability.
Wayne C. Westerman, David P. M. Northmore, John. G. Elias   +2 more
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Stretchable Transistor‐Structured Artificial Synapses for Neuromorphic Electronics

Small, 2023
AbstractStretchable synaptic transistors, a core technology in neuromorphic electronics, have functions and structures similar to biological synapses and can concurrently transmit signals and learn. Stretchable synaptic transistors are usually soft and stretchy and can accommodate various mechanical deformations, which presents significant prospects in
Xiumei Wang, Huihuang Yang, Enlong Li, Chunbin Cao, Wen Zheng, Huipeng Chen, Wenwu Li   +6 more
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An Oxide Schottky Junction Artificial Optoelectronic Synapse

ACS Nano, 2019
The rapid development of artificial intelligence techniques and future advanced robot systems sparks emergent demand on the accurate perception and understanding of the external environments via visual sensing systems that can co-locate the self-adaptive detecting, processing, and memorizing of optical signals. In this contribution, a simple indium-tin
Shuang Gao, Gang Liu, Huali Yang, Chao Hu, Qilai Chen, Guodong Gong, Wuhong Xue, Xiaohui Yi, Jie Shang, Run-Wei Li   +9 more
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Non‐linear Processing in Artificial Synapses

Kybernetes, 1992
Analyses the possibility of allowing non‐linear synaptic processing in Artificial Neural Networks (ANN) both theoretically and practically. The simple computer simulations described strongly suggest that this is a viable alternative, and preferable to ANN with just linear synapses, because of the savings in hardware (fewer components are needed) and ...
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Emerging memory devices for artificial synapses

Journal of Materials Chemistry C, 2020
This paper reviews recent developments in artificial synapses that exploit various emerging memory devices. The emulation of synaptic plasticity and operation mechanism of artificial synapses using various materials and structures are presented.
Youngjun Park, Min-Kyu Kim, Jang-Sik Lee
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Lithium Ion Alloying-Type Artificial Synapses

ACS Applied Electronic Materials, 2019
This paper proposes an artificial synapse (AS) based on the alloying-type behavior of lithium ions (Li+) to govern ion migration and thereby adjust synaptic weights in artificial synaptic devices.
Huanhuan Wei, Haiyang Yu, Jiangdong Gong, Jie Zhang, Hong Han, Mingxue Ma, Yao Ni, Yi Du, Shuo Zhang, Lu Liu, Wentao Xu   +10 more
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Amperometric Detection of Exocytosis in an Artificial Synapse

Analytical Chemistry, 2003
A liposome model of exocytosis has been used to examine the nanometer environment of the space between the electrode and the membrane. First, this has been used to test models of coulometric efficiency for different size vesicles with 5- and 33-microm electrodes.
Ann-Sofie, Cans, Nathan, Wittenberg, Daniel, Eves, Roger, Karlsson, Anders, Karlsson, Owe, Orwar, Andrew, Ewing   +6 more
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Engineer neuromimetic artificial synapses.

Proceedings of the Neuromorphic Materials, Devices, Circuits and Systems, 2023
claudia lubrano, ugo bruno, chiara ausilio, francesca santoro   +3 more
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Multi-ReRAM Synapses for Artificial Neural Network Training

2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019
Metal-oxide-based resistive memory devices (ReRAM) are being actively researched as synaptic elements of neuromorphic co-processors for training deep neural networks (DNNs). However, device-level non-idealities are posing significant challenges. In this work we present a multi-ReRAM-based synaptic architecture with a counter-based arbitration scheme ...
Boybat I., Giovinazzo C., Shahrabi E., Krawczuk I., Giannopoulos I., Piveteau C., Le Gallo M., Ricciardi C., Sebastian A., Eleftheriou E., Leblebici Y.   +10 more
openaire   +1 more source