Results 131 to 140 of about 1,560,355 (287)
Toward Mechanical Intelligence in Robotics
Advanced Robotics Research, EarlyView.Robots can use their physical bodies to perform functions usually assigned to electronic sensors and controllers. This perspective defines mechanical intelligence through three core operations: filtering inputs, routing mechanical signals, and switching between states.
Xinyi Yang +5 more
wiley +1 more source
, 2007 Noise has been a major limitation to partial discharge (PD) measurement. It is crucial to suppress noise prior to any PD data analysis. Recent research shows that the Discrete Wavelet Transform, Wavelet Packet Transform and Stationary Wavelet Transform ...
Zhou, C., Stewart, B. C., Zhou, X.
core +2 more sources
Applied SciencesWavelet transform is a powerful time-frequency-based analysis method often used in gear fault diagnostics. The development of wavelet transform is closely linked to the improvement of resolution.
Trong-Du Nguyen, Phong-Dien Nguyen
doaj +1 more source
Hybrid Deep Learning and Discrete Wavelet Transform-Based ECG Biometric Recognition for Arrhythmic Patients and Healthy Controls. [PDF]
Sensors (Basel), 2023 Asif MS +6 more
europepmc +1 more source
Advanced Robotics Research, EarlyView.A balanced multimodal food‐waste dataset and a novel Split Spatial‐Spectral Attention fusion framework are presented for robotic contaminant detection. Separate processing of RGB, thermal, and multispectral inputs preserves subtle material signatures before feature integration, reducing modality interference and improving classification and ...
Matthew Vestal +5 more
wiley +1 more source
Screening of Discrete Wavelet Transform Parameters for the Denoising of Rolling Bearing Signals in Presence of Localised Defects. [PDF]
Sensors (Basel), 2022 Brusa E +3 more
europepmc +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
Advanced Science, EarlyView.The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
Using discrete wavelet transform for optimizing COVID-19 new cases and deaths prediction worldwide with deep neural networks. [PDF]
PLoS One, 2023 Sperandio Nascimento EG +3 more
europepmc +1 more source
The main purpose of the present work is to estimate the Hurst parameter in real-time as a measure of network traffic self-similarity. There are many possible solutions for Hurst parameter estimation, but in this research the discrete wavelet transform ...
Grabs, Elans, Pētersons, Ernests
core
Advanced Science, EarlyView.NeuroSuite provides a modular hardware‐software platform integrating Neuroweb and NeuroMaps to enable long‐term, in situ electrophysiological interrogation of air–liquid interface organoid slices while preserving tissue architecture. Its components can be used together or independently to capture real‐time activity, spatial network dynamics, and ...
Belquis Haider +14 more
wiley +1 more source