{"id":"https://openalex.org/W2170014524","doi":"https://doi.org/10.1109/lsp.2010.2071383","title":"Multichannel Sampling and Reconstruction of Bandlimited Signals in Fractional Fourier Domain","display_name":"Multichannel Sampling and Reconstruction of Bandlimited Signals in Fractional Fourier Domain","publication_year":2010,"publication_date":"2010-09-07","ids":{"openalex":"https://openalex.org/W2170014524","doi":"https://doi.org/10.1109/lsp.2010.2071383","mag":"2170014524"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2010.2071383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2010.2071383","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/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":null,"affiliations":[{"raw_affiliation_string":"Communication Research Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067948936","display_name":"Yonggang Chi","orcid":"https://orcid.org/0000-0002-3418-1992"},"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":"Yonggang Chi","raw_affiliation_strings":["Communication Research Center, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Research Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103452615","display_name":"Naitong Zhang","orcid":null},"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":"Naitong Zhang","raw_affiliation_strings":["Communication Research Center, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"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":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":7.3468,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":{"value":0.98022038,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"17","issue":"11","first_page":"909","last_page":"912"},"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.9973000288009644,"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":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bandlimiting","display_name":"Bandlimiting","score":0.9473445415496826},{"id":"https://openalex.org/keywords/nyquist\u2013shannon-sampling-theorem","display_name":"Nyquist\u2013Shannon sampling theorem","score":0.7814372777938843},{"id":"https://openalex.org/keywords/nonuniform-sampling","display_name":"Nonuniform sampling","score":0.7068647146224976},{"id":"https://openalex.org/keywords/spectral-leakage","display_name":"Spectral leakage","score":0.6808116436004639},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.6634453535079956},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6153556108474731},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.6005045771598816},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5368587970733643},{"id":"https://openalex.org/keywords/convolution-theorem","display_name":"Convolution theorem","score":0.5356200933456421},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5318509936332703},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.5252906084060669},{"id":"https://openalex.org/keywords/discrete-time-fourier-transform","display_name":"Discrete-time Fourier transform","score":0.4975567162036896},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4741976857185364},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45479753613471985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.36848026514053345},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.33961886167526245},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.2958710789680481},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.2707573175430298},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14176863431930542},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.13677102327346802},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1113041341304779},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.07387775182723999}],"concepts":[{"id":"https://openalex.org/C129997835","wikidata":"https://www.wikidata.org/wiki/Q806263","display_name":"Bandlimiting","level":3,"score":0.9473445415496826},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.7814372777938843},{"id":"https://openalex.org/C20326153","wikidata":"https://www.wikidata.org/wiki/Q7049638","display_name":"Nonuniform sampling","level":3,"score":0.7068647146224976},{"id":"https://openalex.org/C113407356","wikidata":"https://www.wikidata.org/wiki/Q1431214","display_name":"Spectral leakage","level":3,"score":0.6808116436004639},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.6634453535079956},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6153556108474731},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.6005045771598816},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5368587970733643},{"id":"https://openalex.org/C79587385","wikidata":"https://www.wikidata.org/wiki/Q2638931","display_name":"Convolution theorem","level":5,"score":0.5356200933456421},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5318509936332703},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.5252906084060669},{"id":"https://openalex.org/C122444316","wikidata":"https://www.wikidata.org/wiki/Q1440048","display_name":"Discrete-time Fourier transform","level":5,"score":0.4975567162036896},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4741976857185364},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45479753613471985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36848026514053345},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.33961886167526245},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.2958710789680481},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.2707573175430298},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14176863431930542},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.13677102327346802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1113041341304779},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.07387775182723999},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2010.2071383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2010.2071383","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W606473257","https://openalex.org/W1568450818","https://openalex.org/W1988588397","https://openalex.org/W2000076756","https://openalex.org/W2008169417","https://openalex.org/W2040199575","https://openalex.org/W2066825663","https://openalex.org/W2082819064","https://openalex.org/W2099006587","https://openalex.org/W2109257977","https://openalex.org/W2110063971","https://openalex.org/W2111121062","https://openalex.org/W2145576488","https://openalex.org/W2145682890","https://openalex.org/W2156902662","https://openalex.org/W2170411504","https://openalex.org/W2199807983"],"related_works":["https://openalex.org/W1986528019","https://openalex.org/W1495218064","https://openalex.org/W2026890628","https://openalex.org/W3209017587","https://openalex.org/W2050463697","https://openalex.org/W4288358497","https://openalex.org/W2170014524","https://openalex.org/W1974020183","https://openalex.org/W1982270967","https://openalex.org/W2963762854"],"abstract_inverted_index":{"The":[0,43,60,85,115],"classical":[1,86],"multichannel":[2,53,87],"sampling":[3,54,88,93],"theorem":[4,55,61,89,94,111],"for":[5,56,95],"common":[6],"bandlimited":[7,15,58],"signals":[8,16],"has":[9],"been":[10],"extended":[11],"differently":[12],"to":[13,49,83,100],"fractional":[14,20,57],"associated":[17],"with":[18],"the":[19,25,35,66,70,75,91,96,118],"Fourier":[21],"transform":[22],"(FRFT).":[23],"However,":[24],"implementation":[26],"of":[27,34,37,45,77,104,109,117],"those":[28],"existing":[29],"extensions":[30],"is":[31,48,63,81,121],"inefficient":[32],"because":[33],"effect":[36,76],"spectral":[38,78],"leakage":[39,79],"and":[40,80,90],"hardware":[41],"complexity.":[42],"purpose":[44],"this":[46,110],"letter":[47],"introduce":[50],"a":[51],"practical":[52],"signals.":[59],"which":[62],"constructed":[64],"by":[65],"ordinary":[67],"convolution":[68],"in":[69],"time":[71],"domain":[72],"can":[73],"reduce":[74],"easy":[82],"implement.":[84],"well-known":[92],"FRFT":[97],"are":[98,112],"shown":[99],"be":[101],"special":[102],"cases":[103],"it.":[105],"Some":[106],"potential":[107],"applications":[108],"also":[113],"presented.":[114],"validity":[116],"theoretical":[119],"derivations":[120],"demonstrated":[122],"via":[123],"simulations.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}