Results 81 to 90 of about 14,001 (185)
Spintronic Neuron Using a Magnetic Tunnel Junction for Low-Power Neuromorphic Computing
IEEE Magnetics Letters7 pages, 5 figures ...
Steven Louis +4 more
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Algorithm-Hardware Co-design for Ultra-Low-Power Machine Learning and Neuromorphic Computing
, 2023 The rapid proliferation of the Internet of Things (IoT) devices and the growing demand for intelligent systems have driven the development of low-power, compact, and efficient machine learning solutions. Deep neural networks (DNNs) have become state-of-the-art algorithms in various applications, such as face recognition, object detection, and speech ...
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NeuroPong: the event-based camera driven embedded neuromorphic system
Neuromorphic Computing and EngineeringNeuromorphic computing is a novel style of computing that features low-power spiking neural networks (SNNs) as the main compute components. It is an event-driven computational paradigm that naturally pairs with event-based cameras and their asynchronous ...
Charles P Rizzo +9 more
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Design of Memristor Based Modified Synapse Circuit for Low-Power Neuromorphic Computing
Abstract It is high time that brain-inspired or neuromorphic computing must have enough concentration to grow and overcome the computational barrier, which will mimic the biological neuron cell, and its computational abilities will be applied from the neuroscience point of view.
Tarif Ahammad Fuad Hazari +2 more
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Small ScienceBiomimetic neuromorphic optoelectronics exude tempting attraction in multimodal interaction and visual applications because of their capability of integrating sensing, memorizing, and processing in a single device. Herein, a natural dextran film that is intrinsically green and transparent is employed as the dielectric of the optoelectronic synaptic ...
Bo Huang +10 more
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Advanced Electronic MaterialsEfficient computing systems require low‐power and high‐density memory technologies capable of supporting advanced applications such as neuromorphic computing and artificial intelligence. Hafnium oxide (HfO2) based resistive random‐access memory (RRAM) is
Taewook Kim +10 more
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2D Spintronics for Neuromorphic Computing with Scalability and Energy Efficiency
Journal of Low Power Electronics and ApplicationsThe demand for computing power has been growing exponentially with the rise of artificial intelligence (AI), machine learning, and the Internet of Things (IoT).
Douglas Z. Plummer +5 more
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Neuromorphic Computing for IoT: Ultra-Low Power AI for Real-Time Intelligence
International Journal For Multidisciplinary ResearchNeuromorphic computing presents a promising approach for enabling artificial intelligence capabilities in Internet of Things (IoT) devices with stringent power constraints. This paper explores the potential of neuromorphic architectures to deliver ultra-low power AI for real-time intelligence in IoT applications.
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The backpropagation algorithm implemented on spiking neuromorphic hardware
Nature CommunicationsThe capabilities of natural neural systems have inspired both new generations of machine learning algorithms as well as neuromorphic, very large-scale integrated circuits capable of fast, low-power information processing. However, it has been argued that
Alpha Renner +4 more
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Optimization strategy of the emerging memristors: From material preparation to device applications
iScienceSummary: With the advent of the post-Moore era and the era of big data, advanced data storage and processing technology are in urgent demand to break the von Neumann bottleneck.
Kaiyun Gou +4 more
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