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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
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Low-Power Memristor for Neuromorphic Computing: From Materials to Applications
Nano-Micro LettersAs 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 +5 more
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Essential Characteristics of Memristors for Neuromorphic Computing
Advanced Electronic Materials, 2023 The memristor is a resistive switch where its resistive state is programable based on the applied voltage or current. Memristive devices are thus capable of storing and computing information simultaneously, breaking the Von Neumann bottleneck.
Wenbin Chen +6 more
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Room-temperature valley transistors for low-power neuromorphic computing
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 +9 more
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Nature CommunicationsDeveloping 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 +14 more
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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 +7 more
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Low‐Power, Electrochemically Tunable Graphene Synapses for Neuromorphic Computing
Advanced Materials, 2018 AbstractBrain‐inspired neuromorphic computing has the potential to revolutionize the current computing paradigm with its massive parallelism and potentially low power consumption. However, the existing approaches of using digital complementary metal–oxide–semiconductor devices (with “0” and “1” states) to emulate gradual/analog behaviors in the neural ...
Mohammad Taghi Sharbati +2 more
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A ferroelectric-ionic-trapping transistor for low power and secure neuromorphic computing
Nature CommunicationsThe convergence of artificial intelligence and pervasive data analytics has created an urgent demand for energy-efficient and secure computing hardware.
Changhyeon Han +11 more
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Advanced ScienceConventional software‐based encryption faces mounting limitations in power efficiency and security, inspiring the development of emerging neuromorphic computing hardware encryption.
Bo Sun +3 more
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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 +6 more
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