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Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series
In this paper, we propose a fully unsupervised deep learning framework that is able to extract a meaningful and sparse representation of raw HF signals.
Robust Time Series Denoising with Learnable Wavelet Packet Transform
We show that the learnable wavelet packet transform has the learning capabilities of deep learning methods while maintaining the robustness of standard signal processing approaches.
Vacuum Circuit Breaker Closing Time Key Moments Detection via Vibration Monitoring: A Run-to-Failure Study
A key to ensure a reliable operation of CBs is to monitor their condition.
A Comparison of Residual-based Methods on Fault Detection
Fault detection is achieved by applying a threshold that is determined based on the healthy condition.
Uncertainty-Guided Alignment for Unsupervised Domain Adaptation in Regression
Our approach serves a dual purpose: providing a measure of confidence in predictions and acting as a regularization of the embedding space.
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