Ferroelectric synapse hardware supports adaptive spiking neural networks for subject-specific EEG motor imagery classification with accuracy comparable to software versions.
PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Unsupervised discriminator-guided fine-tuning of a pretrained u-sleep model improves Cohen's kappa by 0.03-0.29 on artificially degraded sleep signals but falls short of supervised optima and yields insignificant gains on real domain mismatches.
citing papers explorer
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Personalized Spiking Neural Networks with Ferroelectric Synapses for EEG Signal Processing
Ferroelectric synapse hardware supports adaptive spiking neural networks for subject-specific EEG motor imagery classification with accuracy comparable to software versions.
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Unsupervised domain transfer: Overcoming signal degradation in sleep monitoring by increasing scoring realism
Unsupervised discriminator-guided fine-tuning of a pretrained u-sleep model improves Cohen's kappa by 0.03-0.29 on artificially degraded sleep signals but falls short of supervised optima and yields insignificant gains on real domain mismatches.