Editorial: Neuromorphic and deep learning paradigms for neural data interpretation and computational neuroscience. [PDF]
Front Comput NeurosciZou C, Yuan R, Wen J.
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Analog spike-based neuromorphic computing for low-power smart IoT applications
As the Internet of Things (IoT) expands with more connected devices and complex communications, the demand for precise, energy-efficient localization technologies has intensified. Traditional machine learning and artificial intelligence (AI) techniques provide high accuracy in radio-frequency (RF) localization but often at the cost of greater ...
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Biologically inspired neuromorphic-XAI synergy for transparent and low-carbon healthcare intelligence. [PDF]
Sci RepSungheetha A +5 more
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Bridging neuromorphic computing and deep learning for next-generation neural data interpretation. [PDF]
Front Comput NeurosciZhang M, Wang T, Zhu Z.
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Dedicated and Reconfigurable Artificial Neurons and Synapses based on Two-Dimensional Materials for Efficient Neuromorphic Application. [PDF]
Nanomicro LettChen D +12 more
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Recent progress in HfO<sub>2</sub>-based ferroelectric devices with oxide semiconductor channels: a comprehensive review. [PDF]
Nanoscale AdvKang HY +4 more
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Self-Powered Neuromorphic Touch Sensors Based on Triboelectric Devices: Current Approaches and Open Challenges. [PDF]
SmallTorricelli F, Pace G.
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Ferroelectric nanodot reservoir for neuromorphic computing. [PDF]
Beilstein J NanotechnolRazumnaya A +5 more
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Advancing neuroengineering with Neuromorphic Twins. [PDF]
Nat CommunChiappalone M, Levi T.
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Fabrication of Stochastic Ni@PVP Nanowire Networks for Memristive Platforms. [PDF]
Polymers (Basel)Lemos C, Dias C, Costa RS, Ventura J.
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