Results 21 to 30 of about 4,441 (253)
The Intel neuromorphic DNS challenge
Neuromorphic Computing and Engineering, 2023 A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different neuromorphic solutions on important tasks and to compare them to state-of-the-art conventional solutions.
Jonathan Timcheck +7 more
doaj +1 more source
Bio‐Voltage Memristors: From Physical Mechanisms to Neuromorphic Interfaces
Advanced Electronic Materials, 2023 With the rapid development of emerging artificial intelligence technology, brain–computer interfaces are gradually moving from science fiction to reality, which has broad application prospects in the field of intelligent robots.
Saisai Wang +5 more
doaj +1 more source
Halide perovskite for low‐power consumption neuromorphic devices
EcoMat, 2021 The rapid emergency of data science, information technology, and artificial intelligence (AI) relies on massive data processing with high computing efficiency and low power consumption.
Itaru Raifuku +9 more
doaj +1 more source
Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency
2020 11th International Green and Sustainable Computing Workshops (IGSC), 2020 Neuromorphic computing offers one path forward for AI at the edge. However, accessing and effectively utilizing a neuromorphic hardware platform is non-trivial. In this work, we present a complete pipeline for neuromorphic computing at the edge, including a small, inexpensive, low-power, FPGA-based neuromorphic hardware platform, a training algorithm ...
Catherine D. Schuman +6 more
openaire +2 more sources
Science and Technology of Advanced Materials, 2023 The traditional von Neumann architecture is gradually failing to meet the urgent need for highly parallel computing, high-efficiency, and ultra-low power consumption for the current explosion of data.
Yi Zhang, Zhuohui Huang, Jie Jiang
doaj +1 more source
Complementary Metal‐Oxide Semiconductor and Memristive Hardware for Neuromorphic Computing
Advanced Intelligent Systems, 2020 The ever‐increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing, which takes inspiration from the highly parallel, low‐power, high‐speed,
Mostafa Rahimi Azghadi +10 more
doaj +1 more source
Neuromorphic computing facilitates deep brain-machine fusion for high-performance neuroprosthesis
Frontiers in Neuroscience, 2023 Brain-machine interfaces (BMI) have developed rapidly in recent years, but still face critical issues such as accuracy and stability. Ideally, a BMI system would be an implantable neuroprosthesis that would be tightly connected and integrated into the ...
Yu Qi, Jiajun Chen, Yueming Wang
doaj +1 more source
Reconfigurable neuromorphic memristor network for ultralow-power smart textile electronics
Nature Communications, 2022 Neuromorphic computing memristors are attractive to construct low-power- consumption electronic textiles. Here, authors report an ultralow-power textile memristor network of Ag/MoS2/HfAlOx/carbon nanotube with reconfigurable characteristics and firing ...
Tianyu Wang +15 more
doaj +1 more source
Neuromorphic Computing for Low-Power Artificial Intelligence
CoRRPublished in "2025 Winter Bridge on the Grainger Foundation Frontiers of Engineering" available at https://www.nae.edu/344313/neuromorphic-computing-for-low-power-artificial ...
Keshava Katti +2 more
openaire +2 more sources
Advanced Electronic Materials, 2023 Neuromorphic computing employs a great number of artificial synapses which transfer information between neurons. Conventional two‐ or three‐terminal artificial synapses with homosynaptic plasticity suffer from a positive feedback loop problem.
Fengben Xi +6 more
doaj +1 more source