{"id":"https://openalex.org/W3049512377","doi":"https://doi.org/10.1109/lsp.2020.3016185","title":"Convolutional PCA for Multiple Time Series","display_name":"Convolutional PCA for Multiple Time Series","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3049512377","doi":"https://doi.org/10.1109/lsp.2020.3016185","mag":"3049512377"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.3016185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3016185","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/A5100639669","display_name":"Xi-Lin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xi-Lin Li","raw_affiliation_strings":["GMEMS Technologies, Inc., Milpitas, USA"],"raw_orcid":"https://orcid.org/0000-0002-9939-2176","affiliations":[{"raw_affiliation_string":"GMEMS Technologies, Inc., Milpitas, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100639669"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1485,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.42483836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"27","issue":null,"first_page":"1450","last_page":"1454"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9901000261306763,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9876000285148621,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.818925678730011},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.695593535900116},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6903925538063049},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6352124810218811},{"id":"https://openalex.org/keywords/aliasing","display_name":"Aliasing","score":0.6277031898498535},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.5899745225906372},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5793790221214294},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5727075934410095},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5567910075187683},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5072066783905029},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5027449131011963},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4731755554676056},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4713318347930908},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43951475620269775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3768293857574463},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3546144366264343},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30332738161087036},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1637057363986969},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.07989788055419922}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.818925678730011},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.695593535900116},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6903925538063049},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6352124810218811},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.6277031898498535},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.5899745225906372},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5793790221214294},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5727075934410095},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5567910075187683},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5072066783905029},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5027449131011963},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4731755554676056},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4713318347930908},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43951475620269775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3768293857574463},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3546144366264343},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30332738161087036},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1637057363986969},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.07989788055419922},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2020.3016185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3016185","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1534408902","https://openalex.org/W1975900269","https://openalex.org/W2006916390","https://openalex.org/W2025134436","https://openalex.org/W2033728423","https://openalex.org/W2046317813","https://openalex.org/W2069052473","https://openalex.org/W2098004870","https://openalex.org/W2098301339","https://openalex.org/W2133515443","https://openalex.org/W2295124130","https://openalex.org/W2466299320","https://openalex.org/W2516878419","https://openalex.org/W2604744755","https://openalex.org/W3016175113","https://openalex.org/W3104316338"],"related_works":["https://openalex.org/W2782295999","https://openalex.org/W2006750848","https://openalex.org/W2162306796","https://openalex.org/W1970292246","https://openalex.org/W2356969591","https://openalex.org/W4247952185","https://openalex.org/W1895367623","https://openalex.org/W1642462315","https://openalex.org/W2015118744","https://openalex.org/W2005619368"],"abstract_inverted_index":{"We":[0,70,95],"study":[1,81],"a":[2,13],"fundamental":[3],"generalization":[4],"of":[5,16,30,33,88],"principal":[6,21],"component":[7],"analysis":[8],"(PCA)":[9],"that":[10],"looks":[11],"for":[12,77,107],"small":[14],"set":[15],"common":[17],"time":[18,36,63],"series,":[19],"i.e.,":[20],"components":[22],"(PCs),":[23],"whose":[24],"filtered":[25],"versions":[26],"can":[27],"explain":[28],"most":[29],"the":[31,45,119],"variances":[32],"multiple":[34],"observed":[35],"series.":[37],"This":[38],"problem":[39],"boils":[40],"down":[41],"to":[42,114],"PCA":[43],"in":[44,48,84],"frequency":[46,51],"domain,":[47],"principle.":[49],"But,":[50],"domain":[52,64],"processing":[53],"suffers":[54],"from":[55],"aliasing,":[56],"and":[57,68,74,80,100,103],"brings":[58],"inconveniences":[59],"when":[60],"handling":[61],"certain":[62],"properties":[65,83],"like":[66],"nonstationarity,":[67],"sparsity.":[69],"propose":[71],"novel":[72],"time,":[73],"z-domain":[75],"costs":[76],"such":[78],"PCA,":[79],"its":[82,98],"detail":[85],"with":[86],"setting":[87],"either":[89],"finite":[90],"or":[91],"diverging":[92],"filter":[93],"lengths.":[94],"further":[96],"discuss":[97],"implementations,":[99],"possible":[101],"extensions,":[102],"present":[104],"numerical":[105],"results":[106],"empirical":[108],"performance":[109],"study.":[110],"Convolution":[111],"is":[112],"used":[113],"extract":[115],"these":[116],"PCs,":[117],"thus":[118],"name":[120],"convolutional":[121],"PCA.":[122]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
