{"id":"https://openalex.org/W7131247519","doi":"https://doi.org/10.1109/tsp.2026.3667516","title":"Generalized Singular Spectrum Analysis Associated With Fractional Fourier Transform","display_name":"Generalized Singular Spectrum Analysis Associated With Fractional Fourier Transform","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7131247519","doi":"https://doi.org/10.1109/tsp.2026.3667516"},"language":null,"primary_location":{"id":"doi:10.1109/tsp.2026.3667516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2026.3667516","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","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/A5084904340","display_name":"Hongxia Miao","orcid":"https://orcid.org/0000-0003-4808-0989"},"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":"Hongxia Miao","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4808-0989","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032530028","display_name":"Jun Shi","orcid":"https://orcid.org/0000-0001-6194-4433"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Shi","raw_affiliation_strings":["Communication Research Center, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0001-6194-4433","affiliations":[{"raw_affiliation_string":"Communication Research Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.4486,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97117996,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"74","issue":null,"first_page":"1249","last_page":"1262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.7350000143051147,"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":0.7350000143051147,"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/T13487","display_name":"Statistical and numerical algorithms","score":0.03680000081658363,"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/T12037","display_name":"Algebraic and Geometric Analysis","score":0.028200000524520874,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.6686999797821045},{"id":"https://openalex.org/keywords/discrete-fourier-transform","display_name":"Discrete Fourier transform (general)","score":0.6060000061988831},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.5530999898910522},{"id":"https://openalex.org/keywords/singular-spectrum-analysis","display_name":"Singular spectrum analysis","score":0.5453000068664551},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.525600016117096},{"id":"https://openalex.org/keywords/discrete-sine-transform","display_name":"Discrete sine transform","score":0.5103999972343445},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.48969998955726624},{"id":"https://openalex.org/keywords/non-uniform-discrete-fourier-transform","display_name":"Non-uniform discrete Fourier transform","score":0.46959999203681946},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4659000039100647},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.4553999900817871}],"concepts":[{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.6686999797821045},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6180999875068665},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.6060000061988831},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.5530999898910522},{"id":"https://openalex.org/C136272165","wikidata":"https://www.wikidata.org/wiki/Q4048889","display_name":"Singular spectrum analysis","level":3,"score":0.5453000068664551},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.525600016117096},{"id":"https://openalex.org/C167058841","wikidata":"https://www.wikidata.org/wiki/Q971039","display_name":"Discrete sine transform","level":5,"score":0.5103999972343445},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.48969998955726624},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.48190000653266907},{"id":"https://openalex.org/C62058723","wikidata":"https://www.wikidata.org/wiki/Q7049066","display_name":"Non-uniform discrete Fourier transform","level":5,"score":0.46959999203681946},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4659000039100647},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C146749787","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete-time signal","level":5,"score":0.451200008392334},{"id":"https://openalex.org/C501101116","wikidata":"https://www.wikidata.org/wiki/Q18378116","display_name":"Multidimensional signal processing","level":4,"score":0.4406999945640564},{"id":"https://openalex.org/C175225751","wikidata":"https://www.wikidata.org/wiki/Q15927242","display_name":"Discrete Fourier series","level":5,"score":0.4343000054359436},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C30049272","wikidata":"https://www.wikidata.org/wiki/Q6555326","display_name":"Spectral density estimation","level":3,"score":0.4271000027656555},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.4032999873161316},{"id":"https://openalex.org/C122444316","wikidata":"https://www.wikidata.org/wiki/Q1440048","display_name":"Discrete-time Fourier transform","level":5,"score":0.3978999853134155},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38999998569488525},{"id":"https://openalex.org/C23548689","wikidata":"https://www.wikidata.org/wiki/Q5282049","display_name":"Discrete frequency domain","level":3,"score":0.3873000144958496},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.3862000107765198},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.37279999256134033},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.365200012922287},{"id":"https://openalex.org/C57640460","wikidata":"https://www.wikidata.org/wiki/Q155208","display_name":"Hankel transform","level":3,"score":0.33559998869895935},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.31470000743865967},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.29670000076293945},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.28139999508857727},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C192853989","wikidata":"https://www.wikidata.org/wiki/Q1006531","display_name":"Discrete Hartley transform","level":5,"score":0.274399995803833},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2621000111103058}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2026.3667516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2026.3667516","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3936540016","display_name":null,"funder_award_id":"62271169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4805045011","display_name":null,"funder_award_id":"62201078","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W131531452","https://openalex.org/W1495573900","https://openalex.org/W2000076756","https://openalex.org/W2000982976","https://openalex.org/W2001012548","https://openalex.org/W2001914975","https://openalex.org/W2007221293","https://openalex.org/W2032407953","https://openalex.org/W2033499985","https://openalex.org/W2080339793","https://openalex.org/W2098502158","https://openalex.org/W2100619198","https://openalex.org/W2110063971","https://openalex.org/W2122438546","https://openalex.org/W2130765509","https://openalex.org/W2133438370","https://openalex.org/W2141262522","https://openalex.org/W2144717556","https://openalex.org/W2145576488","https://openalex.org/W2162510928","https://openalex.org/W2169103119","https://openalex.org/W2589214843","https://openalex.org/W2756373030","https://openalex.org/W2897393734","https://openalex.org/W2913154629","https://openalex.org/W2970444351","https://openalex.org/W3011506235","https://openalex.org/W3013823070","https://openalex.org/W3025065882","https://openalex.org/W3027946011","https://openalex.org/W3084419984","https://openalex.org/W4206763478","https://openalex.org/W4232129301","https://openalex.org/W4312220535","https://openalex.org/W4312688066","https://openalex.org/W4320018462","https://openalex.org/W4376454209","https://openalex.org/W4385252345","https://openalex.org/W4386003865","https://openalex.org/W4392174056","https://openalex.org/W4392203628","https://openalex.org/W4400679560","https://openalex.org/W4401328321","https://openalex.org/W4406946882","https://openalex.org/W4409640755","https://openalex.org/W4411078754","https://openalex.org/W4413967007","https://openalex.org/W4414165770","https://openalex.org/W4414314160","https://openalex.org/W4415178956"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1,165],"study,":[2],"an":[3],"adaptive":[4],"nonstationary":[5,93,197,214],"signal":[6,33,83,94,134,141,147,215],"decomposition":[7,53],"technique":[8],"is":[9,12,29,50,95,171,202,208],"developed,":[10],"which":[11,46,79,101],"associated":[13,204],"with":[14,161,205],"the":[15,21,47,60,64,72,76,81,88,103,106,111,154,159,162,174,188,193,199,218],"singular":[16,51,61,180],"spectrum":[17,74,90,191],"analysis":[18,34],"(SSA)":[19],"and":[20,84,118,139,178,211,235],"discrete":[22,32,77,82],"fractional":[23,175,189],"Fourier":[24,112],"transform":[25,113],"(DFrFT).":[26],"The":[27,108],"SSA":[28,160,201,219],"a":[30,40,92,115,123,167],"data-adaptive":[31],"method":[35],"that":[36,59],"does":[37],"not":[38],"require":[39],"parameter":[41],"model":[42],"in":[43,132,137,153,213],"advance,":[44],"of":[45,63,75,91,105,164,192],"core":[48],"operation":[49],"value":[52],"(SVD).":[54],"It":[55,127,207],"has":[56,128],"been":[57],"proven":[58,183],"values":[62,181],"constructed":[65,172],"Hankel":[66,169],"matrix":[67,170],"are":[68,182,233],"equally":[69],"distributed":[70],"to":[71,184,187,221],"power":[73,89,190],"signal,":[78],"bridges":[80],"time-frequency":[85,125],"analysis.":[86],"However,":[87],"often":[96],"wide-band":[97,144],"or":[98],"even":[99],"non-bandlimited,":[100],"degrades":[102],"performance":[104],"SSA.":[107],"DFrFT":[109,155],"contains":[110],"as":[114,122],"special":[116],"case":[117],"can":[119],"be":[120,185],"regarded":[121],"linear":[124],"representation.":[126],"achieved":[129],"significant":[130],"success":[131],"non-stationary":[133],"processing,":[135],"especially":[136],"radar":[138],"communications":[140],"processing.":[142],"A":[143],"(or":[145,151],"non-bandlimited)":[146],"may":[148],"become":[149],"narrow-band":[150],"bandlimited)":[152],"domain.":[156],"To":[157,195],"enhance":[158],"help":[163],"property,":[166],"new":[168],"using":[173,237],"time-shift":[176],"operation,":[177],"its":[179,222],"related":[186],"sequence.":[194],"handle":[196],"signals,":[198],"generalized":[200],"designed":[203],"DFrFT.":[206],"more":[209],"flexible":[210],"suitable":[212],"processing":[216],"than":[217],"due":[220],"free":[223],"parameter.":[224],"Its":[225],"superior":[226],"performances":[227],"over":[228],"other":[229],"popular":[230],"data-driven":[231],"methods":[232],"verified":[234],"displayed":[236],"simulations.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2026-02-25T00:00:00"}
