{"id":"https://openalex.org/W3091374858","doi":"https://doi.org/10.1109/access.2020.3028145","title":"A Robust Random Noise Suppression Method for Seismic Data Using Sparse Low-Rank Estimation in the Time-Frequency Domain","display_name":"A Robust Random Noise Suppression Method for Seismic Data Using Sparse Low-Rank Estimation in the Time-Frequency Domain","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3091374858","doi":"https://doi.org/10.1109/access.2020.3028145","mag":"3091374858"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3028145","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3028145","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2020.3028145","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034956795","display_name":"Pingping Bing","orcid":"https://orcid.org/0000-0001-6956-2819"},"institutions":[{"id":"https://openalex.org/I165911609","display_name":"Changsha Medical University","ror":"https://ror.org/05dt7z971","country_code":"CN","type":"education","lineage":["https://openalex.org/I165911609"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pingping Bing","raw_affiliation_strings":["Academician Workstation, Changsha Medical University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-6956-2819","affiliations":[{"raw_affiliation_string":"Academician Workstation, Changsha Medical University, Changsha, China","institution_ids":["https://openalex.org/I165911609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431965","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0003-2702-0362"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2702-0362","affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100393618","display_name":"Zhihua Zhang","orcid":"https://orcid.org/0000-0003-4391-9896"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihua Zhang","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4391-9896","affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2875,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.5659756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"183546","last_page":"183556"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11757","display_name":"Seismic Waves and Analysis","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.7658942341804504},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6697424650192261},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6108207702636719},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.597955048084259},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5586816072463989},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5355847477912903},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.502924382686615},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4684683680534363},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.45247000455856323},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.44919466972351074},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4326492249965668},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.42967426776885986},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.42181581258773804},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4149585962295532},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.412839412689209},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39801496267318726},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.3602711856365204},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2848259508609772},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2416296899318695},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09389570355415344},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07940301299095154}],"concepts":[{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.7658942341804504},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6697424650192261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6108207702636719},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.597955048084259},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5586816072463989},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5355847477912903},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.502924382686615},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4684683680534363},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.45247000455856323},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.44919466972351074},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4326492249965668},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.42967426776885986},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.42181581258773804},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4149585962295532},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.412839412689209},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39801496267318726},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.3602711856365204},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2848259508609772},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2416296899318695},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09389570355415344},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07940301299095154},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3028145","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3028145","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ffefff49e17c4020885d612d15b1f487","is_oa":true,"landing_page_url":"https://doaj.org/article/ffefff49e17c4020885d612d15b1f487","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 183546-183556 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3028145","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3028145","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5460922556","display_name":null,"funder_award_id":"19C0185","funder_id":"https://openalex.org/F4320333642","funder_display_name":"Scientific Research Foundation of Hunan Provincial Education Department"}],"funders":[{"id":"https://openalex.org/F4320333642","display_name":"Scientific Research Foundation of Hunan Provincial Education Department","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1986754283","https://openalex.org/W1996098514","https://openalex.org/W2000982976","https://openalex.org/W2002777061","https://openalex.org/W2007221293","https://openalex.org/W2011510652","https://openalex.org/W2020205028","https://openalex.org/W2025727209","https://openalex.org/W2061441140","https://openalex.org/W2076393573","https://openalex.org/W2082539625","https://openalex.org/W2090218979","https://openalex.org/W2115528090","https://openalex.org/W2120390927","https://openalex.org/W2125056386","https://openalex.org/W2137832649","https://openalex.org/W2138354688","https://openalex.org/W2141953966","https://openalex.org/W2158824661","https://openalex.org/W2271808722","https://openalex.org/W2280613569","https://openalex.org/W2319436931","https://openalex.org/W2333984260","https://openalex.org/W2468203014","https://openalex.org/W2508093731","https://openalex.org/W2513292816","https://openalex.org/W2603233227","https://openalex.org/W2744992965","https://openalex.org/W2799914480","https://openalex.org/W2801783184","https://openalex.org/W2809571148","https://openalex.org/W2947739840","https://openalex.org/W2963900505","https://openalex.org/W2965087251","https://openalex.org/W2982565605","https://openalex.org/W2984098265","https://openalex.org/W2995302838","https://openalex.org/W2997138148","https://openalex.org/W3000241683","https://openalex.org/W3003534375","https://openalex.org/W3005474703","https://openalex.org/W3013555385","https://openalex.org/W3099529305","https://openalex.org/W6699914277","https://openalex.org/W6751162285"],"related_works":["https://openalex.org/W4390143385","https://openalex.org/W3089517991","https://openalex.org/W3196545307","https://openalex.org/W2973685100","https://openalex.org/W2507476065","https://openalex.org/W4289291956","https://openalex.org/W2901785792","https://openalex.org/W3192537945","https://openalex.org/W2184500224","https://openalex.org/W2952857461"],"abstract_inverted_index":{"The":[0,156],"noise":[1,17,39,173],"separation":[2],"from":[3],"seismic":[4,21,33,57,176],"data":[5,58,125],"is":[6,59,74,164],"of":[7,136,166],"significant":[8],"importance":[9],"in":[10],"geophysics.":[11],"In":[12],"most":[13],"cases,":[14],"the":[15,20,55,68,71,78,95,102,110,114,118,132,142,161],"random":[16,172],"always":[18],"overlaps":[19],"reflections":[22],"over":[23],"time,":[24],"which":[25],"makes":[26],"it":[27],"challenging":[28],"to":[29,76,93,113,130],"suppress.":[30],"To":[31],"enhance":[32],"signal,":[34],"we":[35],"propose":[36],"a":[37,62,82,86,123],"robust":[38,49],"suppression":[40,174],"method":[41,163],"based":[42],"on":[43],"high-order":[44],"synchrosqueezing":[45],"transform":[46],"(FSSTH)":[47],"and":[48,85,98,126,134,139,150,175],"principal":[50],"component":[51],"analysis":[52,154],"(RPCA).":[53],"Firstly,":[54],"noisy":[56],"transformed":[60],"into":[61,81],"sparse":[63,79,87],"time-frequency":[64],"matrix":[65,84,88,112],"(TFM)":[66],"using":[67],"FSSTH.":[69,120],"Then,":[70],"RPCA":[72],"algorithm":[73],"employed":[75],"decompose":[77],"TFM":[80],"low-rank":[83,111],"that":[89,160],"can":[90,105],"be":[91,106],"used":[92],"depict":[94],"useful":[96],"signal":[97,104,177],"noise,":[99],"respectively.":[100],"Finally,":[101],"denoised":[103],"obtained":[107,157],"by":[108],"back-transforming":[109],"time":[115],"domain":[116],"via":[117],"inverse":[119],"We":[121],"utilize":[122],"synthetic":[124],"two":[127],"field":[128],"datasets":[129],"demonstrate":[131],"robustness":[133],"superiority":[135],"our":[137],"method,":[138],"compare":[140],"with":[141],"conventional":[143],"denoising":[144],"algorithms":[145],"such":[146],"as":[147],"f-x":[148],"denconvolution":[149],"f-x$":[151],"singular":[152],"spectrum":[153],"(SSA).":[155],"results":[158],"indicate":[159],"proposed":[162],"capable":[165],"achieving":[167],"an":[168],"excellent":[169],"tadeoff":[170],"between":[171],"preservation.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}