{"id":"https://openalex.org/W4312652484","doi":"https://doi.org/10.1109/lsp.2022.3231469","title":"Multi-Aspect Streaming Tensor Ring Completion for Dynamic Incremental Data","display_name":"Multi-Aspect Streaming Tensor Ring Completion for Dynamic Incremental Data","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312652484","doi":"https://doi.org/10.1109/lsp.2022.3231469"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2022.3231469","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3231469","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015407738","display_name":"Zhenhao Huang","orcid":"https://orcid.org/0000-0001-5874-7148"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["CN","JP"],"is_corresponding":false,"raw_author_name":"Zhenhao Huang","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China","Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-5874-7148","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070961417","display_name":"Yuning Qiu","orcid":"https://orcid.org/0000-0003-0268-0890"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuning Qiu","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0268-0890","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061696482","display_name":"Jinshi Yu","orcid":"https://orcid.org/0000-0001-7930-5146"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinshi Yu","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090101808","display_name":"Guoxu Zhou","orcid":"https://orcid.org/0000-0003-1187-577X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxu Zhou","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China","Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing, China"],"raw_orcid":"https://orcid.org/0000-0003-1187-577X","affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6808,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67226891,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"29","issue":null,"first_page":"2657","last_page":"2661"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7299546003341675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7246425151824951},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7154290080070496},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6248821020126343},{"id":"https://openalex.org/keywords/ring","display_name":"Ring (chemistry)","score":0.4759751856327057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4708618223667145},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4674352705478668},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4416525661945343},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.4341382086277008},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31572073698043823},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16605639457702637},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13653448224067688}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7299546003341675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7246425151824951},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7154290080070496},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6248821020126343},{"id":"https://openalex.org/C2780378348","wikidata":"https://www.wikidata.org/wiki/Q25351438","display_name":"Ring (chemistry)","level":2,"score":0.4759751856327057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4708618223667145},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4674352705478668},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4416525661945343},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.4341382086277008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31572073698043823},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16605639457702637},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13653448224067688},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2022.3231469","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3231469","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1585854524","display_name":null,"funder_award_id":"62203124","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3882248935","display_name":"\u57fa\u4e8e\u5f20\u91cf\u7f51\u7edc\u8868\u5f81\u7684\u673a\u5668\u5b66\u4e60\u7406\u8bba\u4e0e\u7b97\u6cd5\u7814\u7a76","funder_award_id":"62071132","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4242507082","display_name":null,"funder_award_id":"62203128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4870084479","display_name":null,"funder_award_id":"62073087","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8719025522","display_name":null,"funder_award_id":"61973090","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2024165284","https://openalex.org/W2091449379","https://openalex.org/W2103972604","https://openalex.org/W2147512299","https://openalex.org/W2167167503","https://openalex.org/W2431890537","https://openalex.org/W2742340639","https://openalex.org/W2800391958","https://openalex.org/W2907662941","https://openalex.org/W2918050465","https://openalex.org/W2962708900","https://openalex.org/W2963725088","https://openalex.org/W2979001238","https://openalex.org/W3016075648","https://openalex.org/W3102489672","https://openalex.org/W3168052222","https://openalex.org/W3173891418","https://openalex.org/W3205098874","https://openalex.org/W3214968154","https://openalex.org/W4206319168","https://openalex.org/W4206390268","https://openalex.org/W4214526161","https://openalex.org/W4283079434","https://openalex.org/W4292363360","https://openalex.org/W4293193278","https://openalex.org/W4294233382","https://openalex.org/W4294805335","https://openalex.org/W6717575008","https://openalex.org/W6799358853"],"related_works":["https://openalex.org/W2781510240","https://openalex.org/W2170114491","https://openalex.org/W2950186459","https://openalex.org/W2569661359","https://openalex.org/W2242624680","https://openalex.org/W2136127937","https://openalex.org/W2897298721","https://openalex.org/W4290987221","https://openalex.org/W2890370013","https://openalex.org/W2216309014"],"abstract_inverted_index":{"As":[0],"the":[1,58],"volume":[2],"of":[3],"real-world":[4],"data":[5,25,83,86],"with":[6,41],"numerous":[7],"missing":[8],"entries":[9],"continues":[10],"to":[11,21,39,66,92],"grow":[12],"rapidly,":[13],"tensor":[14,50,60],"completion":[15,52],"has":[16],"been":[17],"a":[18,36,47],"powerful":[19],"tool":[20],"enhance":[22],"such":[23],"flawed":[24],"analysis.":[26],"While":[27],"existing":[28],"methods":[29],"mainly":[30],"consider":[31],"static":[32],"data,":[33,81],"there":[34],"is":[35,55,64],"great":[37],"need":[38],"deal":[40],"streaming":[42,49],"data.":[43],"In":[44],"this":[45],"letter,":[46],"multi-aspect":[48],"ring":[51,61],"(MASTR)":[53],"method":[54],"proposed,":[56],"where":[57],"low-rank":[59],"(TR)":[62],"model":[63],"exploited":[65],"capture":[67],"subspace":[68],"information":[69],"and":[70,84],"transfer":[71],"high-order":[72],"correlations":[73],"between":[74],"multiple":[75],"sub-tensors.":[76],"Experimental":[77],"results":[78],"on":[79],"synthetic":[80],"hyperspectral":[82],"video":[85],"demonstrate":[87],"superior":[88],"recovery":[89],"performance":[90],"compared":[91],"state-of-the-art":[93],"methods.":[94]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
