{"id":"https://openalex.org/W3030221356","doi":"https://doi.org/10.1109/lsp.2020.2997561","title":"Fractional Power Spectrum and Fractional Correlation Estimations for Nonuniform Sampling","display_name":"Fractional Power Spectrum and Fractional Correlation Estimations for Nonuniform Sampling","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3030221356","doi":"https://doi.org/10.1109/lsp.2020.2997561","mag":"3030221356"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.2997561","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2997561","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/A5088616426","display_name":"Jinming Ma","orcid":"https://orcid.org/0000-0002-3122-9719"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinming Ma","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067803447","display_name":"Ran Tao","orcid":"https://orcid.org/0000-0002-5243-7189"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Tao","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101586538","display_name":"Yongzhe Li","orcid":"https://orcid.org/0000-0001-5070-6878"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongzhe Li","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083632340","display_name":"Xuejing Kang","orcid":"https://orcid.org/0000-0002-4088-351X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuejing Kang","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5088616426"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":2.0465,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86508895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"27","issue":null,"first_page":"930","last_page":"934"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied 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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied 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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.993399977684021,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6313486099243164},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6068361401557922},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6026303768157959},{"id":"https://openalex.org/keywords/spectral-density-estimation","display_name":"Spectral density estimation","score":0.5623621344566345},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.5548372268676758},{"id":"https://openalex.org/keywords/nonuniform-sampling","display_name":"Nonuniform sampling","score":0.5103165507316589},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.4947955012321472},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.48442867398262024},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4562976360321045},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4276137948036194},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.41379010677337646},{"id":"https://openalex.org/keywords/fractional-calculus","display_name":"Fractional calculus","score":0.4126882553100586},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3990800380706787},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.29312896728515625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.24610331654548645},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.21146103739738464},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20786529779434204},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.20477482676506042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.07640063762664795}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6313486099243164},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6068361401557922},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6026303768157959},{"id":"https://openalex.org/C30049272","wikidata":"https://www.wikidata.org/wiki/Q6555326","display_name":"Spectral density estimation","level":3,"score":0.5623621344566345},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.5548372268676758},{"id":"https://openalex.org/C20326153","wikidata":"https://www.wikidata.org/wiki/Q7049638","display_name":"Nonuniform sampling","level":3,"score":0.5103165507316589},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.4947955012321472},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.48442867398262024},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4562976360321045},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4276137948036194},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.41379010677337646},{"id":"https://openalex.org/C154249771","wikidata":"https://www.wikidata.org/wiki/Q1339058","display_name":"Fractional calculus","level":2,"score":0.4126882553100586},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3990800380706787},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.29312896728515625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.24610331654548645},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.21146103739738464},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20786529779434204},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.20477482676506042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.07640063762664795},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2020.2997561","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2997561","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/G4417359500","display_name":null,"funder_award_id":"U1833203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4639895821","display_name":null,"funder_award_id":"61421001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7033945759","display_name":null,"funder_award_id":"61901041","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":30,"referenced_works":["https://openalex.org/W1847929618","https://openalex.org/W1965936301","https://openalex.org/W1996838926","https://openalex.org/W2005286627","https://openalex.org/W2007241134","https://openalex.org/W2013913026","https://openalex.org/W2018654957","https://openalex.org/W2025617969","https://openalex.org/W2028675890","https://openalex.org/W2038044778","https://openalex.org/W2041352473","https://openalex.org/W2054613697","https://openalex.org/W2064982323","https://openalex.org/W2066825663","https://openalex.org/W2100619198","https://openalex.org/W2110063971","https://openalex.org/W2149720531","https://openalex.org/W2162504972","https://openalex.org/W2165049638","https://openalex.org/W2170014524","https://openalex.org/W2170182872","https://openalex.org/W2344912857","https://openalex.org/W2508224038","https://openalex.org/W2548592040","https://openalex.org/W2577625856","https://openalex.org/W2652471884","https://openalex.org/W2769390742","https://openalex.org/W2784286678","https://openalex.org/W2795198316","https://openalex.org/W2988070874"],"related_works":["https://openalex.org/W262848098","https://openalex.org/W2015854950","https://openalex.org/W1917904586","https://openalex.org/W2488177955","https://openalex.org/W1488610482","https://openalex.org/W2355015151","https://openalex.org/W2783211270","https://openalex.org/W1935517055","https://openalex.org/W2144045625","https://openalex.org/W3011889258"],"abstract_inverted_index":{"This":[0],"letter":[1],"proposes":[2],"new":[3],"estimations":[4,40],"of":[5,19,43,58,64,79,107,112,123,137,147,152,160],"fractional":[6,12,29,76,114,134,145],"power":[7],"spectral":[8],"density":[9],"(FrPSD)":[10],"and":[11,24,38,60,117,140],"correlation":[13],"function":[14],"(FrCF)":[15],"for":[16,82],"nonuniform":[17],"sampling":[18,47,66,93],"random":[20,85],"signals":[21],"with":[22,45],"non-stationarity":[23],"limited":[25],"bandwidths":[26],"in":[27],"the":[28,35,71,80,83,92,100,105,132,138,144,148,153,158,161],"Fourier":[30,135],"domain.":[31],"Unlike":[32],"previous":[33],"works,":[34],"developed":[36],"FrPSD":[37,61,73,81,101,108],"FrCF":[39,59,126],"are":[41],"capable":[42],"dealing":[44],"unknown":[46],"instants.":[48,67,94],"In":[49],"order":[50],"to":[51,74,103,130],"obtain":[52,119],"them,":[53],"we":[54,69,98],"first":[55],"formulate":[56],"approximations":[57],"making":[62],"use":[63],"uniform":[65],"Then":[68],"convert":[70],"approximate":[72],"a":[75,113,120],"filtered":[77],"version":[78],"original":[84],"signal,":[86],"which":[87],"does":[88],"not":[89],"rely":[90],"on":[91],"With":[95],"such":[96],"operations,":[97],"propose":[99],"estimation":[102,127,163],"cancel":[104],"bias":[106],"approximation":[109,151],"by":[110],"means":[111],"inverse":[115,133],"filtering":[116],"thereby":[118],"high":[121],"accuracy":[122],"it.":[124],"The":[125],"is":[128],"proposed":[129,162],"be":[131],"transform":[136],"FrPSD,":[139],"it":[141],"serves":[142],"as":[143],"interpolation":[146],"previously":[149],"obtained":[150],"FrCF.":[154],"Simulation":[155],"results":[156],"show":[157],"effectiveness":[159],"methods.":[164]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}