Results 51 to 60 of about 7,085,552 (171)

Acoustic Source Localisation of Surface Discharge on Converter Valve Damping Capacitors Based on BSBL and Fuzzy Narrowband Focusing Beamforming

IET Science, Measurement &Technology, Volume 20, Issue 1, January/December 2026.
To address the challenge of accurately localising surface discharge on converter valve damping capacitors, which is hampered by frequency drift and near‐field shielding, this study proposes a novel acoustic localisation method combining fuzzy narrowband focusing with Block Sparse Bayesian Learning (BSBL). Simulation and experimental results demonstrate
Rui Yang, Yunpeng Liu, Yuling Liu, Jianghai Geng, Yimiao Wang, Yi Su   +5 more
wiley   +1 more source

Joint channel and impulse noise estimation based on compressed sensing and Kalman filter for OFDM system

EURASIP Journal on Advances in Signal Processing, 2023
Impulse noise (IN) widely exists in many communication systems, which seriously affects the performance of OFDM communication systems. A joint channel and IN estimation method based on all subcarriers is designed.
Yiting Zhao, Youming Li, Shoudong Shi, Jianding Yu   +3 more
doaj   +1 more source

Infrasound Source Localization of Distributed Stations Using Sparse Bayesian Learning and Bayesian Information Fusion

Remote Sensing, 2022
The precise localization of the infrasound source is important for infrasound event monitoring. The localization of infrasound sources is influenced by the atmospheric propagation environment and infrasound measurement equipment in the large-scale global
Ran Wang, Xiaoquan Yi, Liang Yu, Chenyu Zhang, Tongdong Wang, Xiaopeng Zhang   +5 more
doaj   +1 more source

GS-SBL: Bridging Greedy Pursuit and Sparse Bayesian Learning for Efficient 3D Wireless Channel Modeling

Robust cognitive radio development requires accurate 3D path loss models. Traditional empirical models often lack environment-awareness, while deep learning approaches are frequently constrained by the scarcity of large-scale training datasets. This work leverages the inherent sparsity of wireless propagation to model scenario-specific channels by ...
Rahman, Mushfiqur, Guvenc, Ismail, Matolak, David   +2 more
openaire   +2 more sources

A Bayesian and Laplace Prior‐Based Adaptive Sparse Regularization Approach for Structural Damage Diagnosis With Uncertainty Quantification

Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.
The uncertainties arising from measurement noise and model error in operational structures often render damage detection problems ill‐posed in practical applications. Limited sensor availability and the complexity of real‐world damage scenarios further complicate damage identification.
Jian-Fu Lin, Wei-Lin Wu, Jian-Liang Huang, Jun-Fang Wang, Yi-Qing Ni, Wei-Xin Ren, Yi-Lin Li, Andrea Del Grosso   +7 more
wiley   +1 more source

Wideband Sparse Bayesian Learning for DOA estimation from multiple snapshots

, 2016
The directions of arrival (DOA) of plane waves are estimated from multi-frequency multi-snapshot sensor array data using Sparse Bayesian Learning (SBL).
Peter Gerstoft, Mecklenbräuker, Christoph, Christoph F. Mecklenbrauker, Gerstoft, Peter   +3 more
core   +1 more source

Multi Snapshot Sparse Bayesian Learning for DOA Estimation

, 2017
The directions of arrival (DOA) of plane waves are estimated from multi-snapshot sensor array data using the Sparse Bayesian Learning (SBL) approach. Assuming as prior information independent zero-mean complex Gaussian distributed source amplitudes ...
Mecklenbräuker, Christoph, Xenaki, Angeliki, Gerstoft, Peter   +2 more
core   +2 more sources

Modified SBL-Based Multichannel Radar Forward-Looking Superresolution Imaging of Block-Sparse Targets

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Multichannel radar has the potential of forward-looking imaging with single snapshot data, but its azimuth resolution is usually poor due to the restriction of the platform size.
Wenchao Li, Zhe Zhang, Kefeng Li, Rui Chen, Kun Zhang, Deqing Mao, Jianyu Yang   +6 more
doaj   +1 more source

Sparse Bayesian learning-based mainlobe blanket jamming suppression algorithm

The Journal of Engineering, 2019
The suppression of mainlobe jamming (MLJ) is a hard task and an open problem in the electronic counter-countermeasures field. In this article, a sparse Bayesian learning (SBL)-based mainlobe blanket jamming suppression algorithm is proposed for solving ...
Bilei Zhou, Keqing Duan, Weijian Liu, Rongfeng Li, Yongliang Wang   +4 more
doaj   +1 more source

The combined effects of multiple stressors in an endangered, long‐lived species: Lessons learned and ways forward

Ecological Applications, Volume 35, Issue 8, December 2025.
Abstract Exploring solutions to expanding industrial activities and climate change requires assessments of the combined effects of multiple stressors on wildlife populations. We present a spatially explicit state‐space model for the health, survival, reproduction, and somatic growth of individuals in a long‐lived, wide‐ranging species.
Enrico Pirotta, Peter L. Tyack, Jeffrey Adams, Michael J. Asaro, Phil J. Bouchet, Daniel E. Crocker, John W. Durban, Ailsa J. Hall, Catriona M. Harris, Amy R. Knowlton, Scott D. Kraus, Caroline Lehoux, Daniel W. Linden, Caroline P. Good, Erin Meyer‐Gutbrod, Alicia S. Miller, Carolyn A. Miller, Patrick J. O. Miller, Michael J. Moore, Christopher D. Orphanides, Eric M. Patterson, Heather M. Pettis, Theoni Photopoulou, Stéphane Plourde, Nicholas R. Record, Jessica V. Redfern, Jason J. Roberts, Robert S. Schick, Burton Shank, Laura Solinger, Brandon L. Southall, Marisa L. Trego, Len Thomas   +32 more
wiley   +1 more source