Result: Robust Adaptive Beamforming Based on Linearly Modified Atomic-Norm Minimization With Target Contaminated Data: Robust adaptive beamforming based on linearly modified atomic-norm minimization with target contaminated data

Title:
Robust Adaptive Beamforming Based on Linearly Modified Atomic-Norm Minimization With Target Contaminated Data: Robust adaptive beamforming based on linearly modified atomic-norm minimization with target contaminated data
Authors:
Xinyu Zhang, Weidong Jiang, Kai Huo, Yongxiang Liu, Xiang Li
Source:
IEEE Transactions on Signal Processing. 68:5138-5151
Publisher Information:
Institute of Electrical and Electronics Engineers (IEEE), 2020.
Publication Year:
2020
Subject Terms:
Signal theory (characterization, reconstruction, filtering, etc.), Detection theory in information and communication theory, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Document Type:
Academic journal Article
File Description:
application/xml
ISSN:
1941-0476
1053-587X
DOI:
10.1109/tsp.2020.3021257
Access URL:
https://ieeexplore.ieee.org/document/9187960
https://dblp.uni-trier.de/db/journals/tsp/tsp68.html#ZhangJHLL20
http://ui.adsabs.harvard.edu/abs/2020ITSP...68.5138Z/abstract
Rights:
IEEE Copyright
publisher-specific, author manuscript
Accession Number:
edsair.doi.dedup.....f0aa55daf0dc4a7faffa8f6b3c472a7f
Database:
OpenAIRE

Further Information

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