Microseismic Source Location Based on Full Waveform Inversion-Driven Neural Network
International Journal of Computational Intelligence SystemsAccurate localization of microseismic sources is essential in fields such as oil and gas extraction and underground energy storage. Current seismic source localization methods based on full waveform inversion exhibit a high degree of nonlinearity and ...
Yan Zhang +6 more
doaj +1 more source
Accurate detection method of traveling wave shape based on EEMD and L1 norm regularization
International Journal of Electrical Power & Energy SystemsAiming at the problem of waveform distortion of the secondary traveling wave obtained from the primary traveling wave signal transmitted by the voltage traveling wave sensor, an accurate detection method of voltage traveling wave based on ensemble ...
Tao Tang +5 more
doaj +1 more source
Full-waveform inversion based on generalized Rényi entropy using patched Green's function techniques. [PDF]
PLoS One, 2022 Barbosa WA +3 more
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Biomimetic 3D Tactile Sensor System With Neuromorphic Encoding for Fascicle‐Level Feedback
Advanced Intelligent Systems, EarlyView.A 3D biomimetic tactile sensor system converts skin‐like mechanical interactions into neural stimulation‐ready spike patterns. Embedded slow‐ and fast‐adapting sensors distinguish sustained pressure from transient touch, while neuromorphic encoding preserves their temporal signatures.
Minseok Kim +4 more
wiley +1 more source
How Does Neural Network Reparametrization Improve Geophysical Inversion?
Journal of Geophysical Research: Machine Learning and ComputationFull waveform inversion (FWI) is a high‐resolution seismic inversion technique and great efforts have been made to mitigate the multi‐solution problem, such as the traditional total variation (TV) regularization. Different from traditional regularization,
Yuping Wu, Jianwei Ma
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Remote SensingGround-penetrating radar (GPR) has emerged as a promising technology for estimating the soil water content (SWC) in the vadose zone. However, most current studies focus on partial GPR data, such as travel-time or amplitude, to achieve SWC estimation ...
Hanqing Qiao, Minghe Zhang, Maksim Bano
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A Forward Model Incorporating Elevation-Focused Transducer Properties for 3-D Full-Waveform Inversion in Ultrasound Computed Tomography. [PDF]
IEEE Trans Ultrason Ferroelectr Freq Control, 2023 Li F, Villa U, Duric N, Anastasio MA.
europepmc +1 more source
Accelerating full waveform inversion by transfer learning
Computational MechanicsAbstract Full waveform inversion (FWI) is a powerful tool for reconstructing material fields based on sparsely measured data obtained by wave propagation. For specific problems, discretizing the material field with a neural network (NN) improves the robustness and reconstruction quality of the corresponding optimization problem.
Divya Shyam Singh 0001 +5 more
openaire +2 more sources
Physics‐Grounded Probabilistic Bits for Hardware‐Efficient Intelligent Inference and Optimization
Advanced Intelligent Systems, EarlyView.Si–SiNx interface traps are harnessed as a complementary metal–oxide–semiconductor‐compatible source of controllable randomness for probabilistic bits. Pulse‐width‐programmed stochastic capture converts nanoscale defect dynamics into Boltzmann‐consistent binary outputs, while a physics‐based Simulation Program with Integrated Circuit Emphasis model ...
Dokyoung Lee +3 more
wiley +1 more source
Deep-Learning-Driven Full-Waveform Inversion for Ultrasound Breast Imaging. [PDF]
Sensors (Basel), 2021 Robins T +4 more
europepmc +1 more source