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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

Emerging memristive neurons for neuromorphic computing and sensing

Science and Technology of Advanced Materials, 2023
Inspired by the principles of the biological nervous system, neuromorphic engineering has brought a promising alternative approach to intelligence computing with high energy efficiency and low consumption.
Zhiyuan Li, Wei Tang, Beining Zhang, Rui Yang, Xiangshui Miao   +4 more
doaj   +3 more sources

Underlying Framework of All-optical Controlled Synaptic Devices for Neuromorphic Computing [PDF]

Nano-Micro Letters
Highlights Neuromorphic computing, using artificial synaptic devices, mimics the structure and function of biological neural networks, offering a solution to the von Neumann bottleneck for the next-generation of artificial intelligence.
Dunan Hu, Ruqi Yang, Zhizhen Ye, Jianguo Lu   +3 more
doaj   +2 more sources

Two-Dimensional MXene-Based Advanced Sensors for Neuromorphic Computing Intelligent Application [PDF]

Nano-Micro Letters
Highlights The latest research progress in the field of MXene-based neuromorphic computing is reviewed. The design strategy of MXene-based neuromorphic devices encompasses multiple factors are summarized, including material selection, circuit integration,
Lin Lu, Bo Sun, Zheng Wang, Jialin Meng, Tianyu Wang   +4 more
doaj   +2 more sources

Neuromorphic Computing for Smart Agriculture

Agriculture
Neuromorphic computing has received more and more attention recently since it can process information and interact with the world like the human brain.
Shize Lu, Xinqing Xiao
doaj   +3 more sources

A Review of Nanowire Devices Applied in Simulating Neuromorphic Computing [PDF]

Nanomaterials
With the rapid advancement of artificial intelligence and machine learning technologies, the demand for enhanced device computing capabilities has significantly increased.
Tianci Huang, Yuxuan Wang, Zhihan Jin, Hao Liu, Kaili Wang, Tan Leong Chee, Yi Shi, Shancheng Yan   +7 more
doaj   +2 more sources

Electrolyte Gated Transistors for Brain Inspired Neuromorphic Computing and Perception Applications: A Review [PDF]

Nanomaterials
Emerging neuromorphic computing offers a promising and energy-efficient approach to developing advanced intelligent systems by mimicking the information processing modes of the human brain.
Weisheng Wang, Liqiang Zhu
doaj   +2 more sources

Physics for neuromorphic computing [PDF]

Nature Reviews Physics, 2020
Neuromorphic computing takes inspiration from the brain to create energy efficient hardware for information processing, capable of highly sophisticated tasks. In this article, we make the case that building this new hardware necessitates reinventing electronics. We show that research in physics and material science will be key to create artificial nano-
Danijela Marković, Alice Mizrahi, Damien Querlioz, Julie Grollier   +3 more
openaire   +2 more sources

Mechanical Properties Analysis of Flexible Memristors for Neuromorphic Computing [PDF]

Nano-Micro Letters
Tian-Yu Wang, Jia-Lin Meng
exaly   +2 more sources

Is Neuromorphic MNIST Neuromorphic? Analyzing the Discriminative Power of Neuromorphic Datasets in the Time Domain

Frontiers in Neuroscience, 2021
A major characteristic of spiking neural networks (SNNs) over conventional artificial neural networks (ANNs) is their ability to spike, enabling them to use spike timing for coding and efficient computing.
Laxmi R. Iyer, Yansong Chua, Haizhou Li, Haizhou Li   +3 more
doaj   +1 more source