Study provides long-term EMG data for multi-day biometric authentication.
arXiv research
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Analyzes multi-day stock returns, showing linear volatility and mean dependence.
Accumulated stock returns exhibit tempered skew t-distribution.
Master thesis applies deep learning to sEMG hand gesture recognition, improving accuracy.
Study compares VaR models and finds GARCH-FHS superior.
LEMs extend transformer-based architectures for complex execution problems.
Hybrid pipeline detects spike-and-wave discharges in long-term EEG recordings.
Existing methods for arterial blood pressure (BP) estimation directly map the input physiological signals to output BP values without explicitly modeling the underlying temporal dependencies in BP dynamics. As a result, these models suffer from accuracy decay over a long time and thus require frequent calibration. In t…
Enhances crowd safety through AI and data-driven models.
Breaks circular dependency in synthetic option pricing with a novel model.