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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Room-temperature valley transistors for low-power neuromorphic computing [PDF]
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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Nanofiber Channel Organic Electrochemical Transistors for Low‐Power Neuromorphic Computing and Wide‐Bandwidth Sensing Platforms [PDF]
Advanced Science, 2021 Organic neuromorphic computing/sensing platforms are a promising concept for local monitoring and processing of biological signals in real time. Neuromorphic devices and sensors with low conductance for low power consumption and high conductance for low ...
Sol‐Kyu Lee +7 more
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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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Low Power Optoelectronic Neuromorphic Memristor for In‐Sensor Computing and Multilevel Hardware Security Communications [PDF]
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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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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Reconfigurable In-Sensor Computing Memristor for Olfactory SNN and Reservoir Hybrid Neuromorphic Computing [PDF]
ResearchTraditional 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 +6 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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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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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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