FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2332956390> ?p ?o ?g. }

• W2332956390 abstract "PreviousNext No AccessSEG Technical Program Expanded Abstracts 2013Seismic deblending by sparse inversion over dictionary learningAuthors: Yanhui ZhouWenchao ChenJinghuai GaoFrossard PascalYanhui ZhouXian Jiaotong USearch for more papers by this author, Wenchao ChenXian Jiaotong USearch for more papers by this author, Jinghuai GaoXian Jiaotong USearch for more papers by this author, and Frossard PascalSwiss Federal Institute of Technology LausanneSearch for more papers by this authorhttps://doi.org/10.1190/segam2013-0269.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract By dictionary learning from trained samples, a set of datadriven dictionary atoms can be obtained and used to favor sparser representation of patched data. In this paper, in the context of the blending framework with time-dithering sequential source shooting and by regarding seismic deblending as an inverse problem, sparse inversion and dictionary learning are combined to construct the corresponding formula of minimization with respect to unknown recovery, dictionary, and coefficient set. And an alternating algorithm is presented and in each iteration, dictionary atoms and coefficients are updated by K singular vector decomposition (K-SVD) method in one step and subsequently the recovery is updated by a fast steepest descent gradient method in the other step. A synthetic and real field data demonstrate the effectiveness of our method. And the outcome can be a significant reference in designing highefficiency and low-cost blending acquisition. Permalink: https://doi.org/10.1190/segam2013-0269.1FiguresReferencesRelatedDetailsCited ByUnsupervised seismic data deblending based on the convolutional autoencoder regularization22 April 2022 | Acta Geophysica, Vol. 70, No. 3Iterative Deblending of Simultaneous-Source Seismic Data via a Robust Singular Spectrum Analysis FilterIEEE Transactions on Geoscience and Remote Sensing, Vol. 60Simultaneous‐source deblending using adaptive coherence‐constrained dictionary learning and sparse approximation31 March 2021 | Geophysical Prospecting, Vol. 69, No. 4Is the sparsity enough? Random noise suppression in prestack seismic data using sparsity and lowrankness simultaneouslyWeiwei Xu*, Wenchao Chen, Yanhui Zhou, Xiaokai Wang, Cheng Wang, Hongxu Wang, and Yi Bao17 January 2020Seismic reconstruction via constrained dictionary learningYanhui Zhou, Wenchao Chen, Zhensheng Shi, and Xiaokai Wang27 August 2018Lobbes: An Algorithm for Sparse-Spike DeconvolutionIEEE Geoscience and Remote Sensing Letters, Vol. 14, No. 12Seismic Simultaneous Source Separation via Patchwise Sparse RepresentationIEEE Transactions on Geoscience and Remote Sensing, Vol. 54, No. 9Deblending 4-component simultaneous-source data – A 2D OBC case study in MalaysiaGuillaume Henin*, Didier Marin, Shivaji Maitra, Anne Rollet, Sandeep Kumar Chandola, Subodh Kumar, Nabil El Kady, and Low Cheng Foo19 August 2015 SEG Technical Program Expanded Abstracts 2013ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2013 Pages: 5258 Publisher:Society of Exploration Geophysicists HistoryPublished: 19 Aug 2013 CITATION INFORMATION Yanhui Zhou, Wenchao Chen, Jinghuai Gao, and Frossard Pascal, (2013), Seismic deblending by sparse inversion over dictionary learning, SEG Technical Program Expanded Abstracts : 273-278. https://doi.org/10.1190/segam2013-0269.1 Plain-Language Summary PDF DownloadLoading ..." @default.
• W2332956390 created "2016-06-24" @default.
• W2332956390 creator A5000947076 @default.
• W2332956390 creator A5015778825 @default.
• W2332956390 creator A5025477117 @default.
• W2332956390 creator A5077552109 @default.
• W2332956390 date "2013-08-19" @default.
• W2332956390 modified "2023-10-18" @default.
• W2332956390 title "Seismic deblending by sparse inversion over dictionary learning" @default.
• W2332956390 cites W1890834058 @default.
• W2332956390 cites W1928784500 @default.
• W2332956390 cites W1997837299 @default.
• W2332956390 cites W2042040926 @default.
• W2332956390 cites W2056388239 @default.
• W2332956390 cites W2066682713 @default.
• W2332956390 cites W2111333160 @default.
• W2332956390 cites W2115528090 @default.
• W2332956390 cites W2160547390 @default.
• W2332956390 cites W2168668658 @default.
• W2332956390 doi "https://doi.org/10.1190/segam2013-0269.1" @default.
• W2332956390 hasPublicationYear "2013" @default.
• W2332956390 type Work @default.
• W2332956390 sameAs 2332956390 @default.
• W2332956390 citedByCount "9" @default.
• W2332956390 countsByYear W23329563902015 @default.
• W2332956390 countsByYear W23329563902016 @default.
• W2332956390 countsByYear W23329563902017 @default.
• W2332956390 countsByYear W23329563902018 @default.
• W2332956390 countsByYear W23329563902020 @default.
• W2332956390 countsByYear W23329563902021 @default.
• W2332956390 countsByYear W23329563902022 @default.
• W2332956390 countsByYear W23329563902023 @default.
• W2332956390 crossrefType "proceedings-article" @default.
• W2332956390 hasAuthorship W2332956390A5000947076 @default.
• W2332956390 hasAuthorship W2332956390A5015778825 @default.
• W2332956390 hasAuthorship W2332956390A5025477117 @default.
• W2332956390 hasAuthorship W2332956390A5077552109 @default.
• W2332956390 hasConcept C109007969 @default.
• W2332956390 hasConcept C11413529 @default.
• W2332956390 hasConcept C124066611 @default.
• W2332956390 hasConcept C127313418 @default.
• W2332956390 hasConcept C134306372 @default.
• W2332956390 hasConcept C135252773 @default.
• W2332956390 hasConcept C147764199 @default.
• W2332956390 hasConcept C151730666 @default.
• W2332956390 hasConcept C153180895 @default.
• W2332956390 hasConcept C153258448 @default.
• W2332956390 hasConcept C154945302 @default.
• W2332956390 hasConcept C1893757 @default.
• W2332956390 hasConcept C199360897 @default.
• W2332956390 hasConcept C22789450 @default.
• W2332956390 hasConcept C2779343474 @default.
• W2332956390 hasConcept C2988886741 @default.
• W2332956390 hasConcept C33923547 @default.
• W2332956390 hasConcept C41008148 @default.
• W2332956390 hasConcept C50644808 @default.
• W2332956390 hasConceptScore W2332956390C109007969 @default.
• W2332956390 hasConceptScore W2332956390C11413529 @default.
• W2332956390 hasConceptScore W2332956390C124066611 @default.
• W2332956390 hasConceptScore W2332956390C127313418 @default.
• W2332956390 hasConceptScore W2332956390C134306372 @default.
• W2332956390 hasConceptScore W2332956390C135252773 @default.
• W2332956390 hasConceptScore W2332956390C147764199 @default.
• W2332956390 hasConceptScore W2332956390C151730666 @default.
• W2332956390 hasConceptScore W2332956390C153180895 @default.
• W2332956390 hasConceptScore W2332956390C153258448 @default.
• W2332956390 hasConceptScore W2332956390C154945302 @default.
• W2332956390 hasConceptScore W2332956390C1893757 @default.
• W2332956390 hasConceptScore W2332956390C199360897 @default.
• W2332956390 hasConceptScore W2332956390C22789450 @default.
• W2332956390 hasConceptScore W2332956390C2779343474 @default.
• W2332956390 hasConceptScore W2332956390C2988886741 @default.
• W2332956390 hasConceptScore W2332956390C33923547 @default.
• W2332956390 hasConceptScore W2332956390C41008148 @default.
• W2332956390 hasConceptScore W2332956390C50644808 @default.
• W2332956390 hasLocation W23329563901 @default.
• W2332956390 hasOpenAccess W2332956390 @default.
• W2332956390 hasPrimaryLocation W23329563901 @default.
• W2332956390 hasRelatedWork W1971373099 @default.
• W2332956390 hasRelatedWork W1972656095 @default.
• W2332956390 hasRelatedWork W1983610137 @default.
• W2332956390 hasRelatedWork W2080597906 @default.
• W2332956390 hasRelatedWork W2157785665 @default.
• W2332956390 hasRelatedWork W2342163728 @default.
• W2332956390 hasRelatedWork W2387902160 @default.
• W2332956390 hasRelatedWork W2750523634 @default.
• W2332956390 hasRelatedWork W2972485657 @default.
• W2332956390 hasRelatedWork W2990531703 @default.
• W2332956390 isParatext "false" @default.
• W2332956390 isRetracted "false" @default.
• W2332956390 magId "2332956390" @default.
• W2332956390 workType "article" @default.