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- W4387411199 abstract "Hyper-Dimensional Computing (HDC), a nanoscalable learning paradigm for low-energy predictions and lightweight models, has seen a surge in interest from the hardware accelerator community. Its statistical and distributed data representation leads to highly-efficient classifiers with inherent robustness to representation errors. A digital, 28nm CMOS chip, representing the first programmable HDC biosignal processor, achieves 25.6 nJ/pred. on a leading EMG gesture recognition dataset. Measurements confirm the high robustness of HDC: a 47% bit error-rate in the datapath by VDD overscaling leads to only 1.37% accuracy drop. This realization is the most efficient and robust EMG gesture classifier to date –its per-channel efficiency is $ 1312times$ that of Artificial Neural Networks and 76 $mathrm{m}mathrm{i}mathrm{l}mathrm{l}mathrm{i}mathrm{o}mathrm{n}times$ that of Spiking Neural Networks." @default.
- W4387411199 created "2023-10-07" @default.
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- W4387411199 date "2023-09-11" @default.
- W4387411199 modified "2023-10-08" @default.
- W4387411199 title "HDBinaryCore: A 28nm 2048-bit Hyper-Dimensional biosignal classifier achieving 25 nJ/prediction for EMG hand-gesture recognition" @default.
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- W4387411199 doi "https://doi.org/10.1109/esscirc59616.2023.10268684" @default.
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