Abstract: Signal as a noise confined to small scales or high frequency can be removed preferentially from noisy signals if some prior information is available. According to the uncertainty principle, ...

Abstract: This study delves into two fault localization techniques in power transmission systems, specifically focusing on the Discrete Wavelet Transform (DWT) and the DifferentiatorSmoother (DS) ...

Wavelet transform techniques have emerged as a powerful tool for analysing signals whose spectral content varies over time. By decomposing a signal into scaled and translated versions of a ...

The wavelet transform (WT) has gained significant attention for its ability to identify damage details within strain modes. However, edge damage in structures often remains obscured and unrecognizable ...

Noise suppression is a key component in microseismic monitoring technology. Accurate denoising of microseismic signals is crucial for ensuring reliable data for locating mining-related seismic events ...

Brain-computer interfaces (BCIs) leverage EEG signal processing to enable human-machine communication and have broad application potential. However, existing deep learning-based BCI methods face two ...

This project focuses on image fusion, a method used to combine multiple images of the same scene into a single, comprehensive version that is more informative than the originals. By employing the ...