{"id":"https://openalex.org/W2739824799","doi":"https://doi.org/10.1109/tsp.2017.2733484","title":"Paley\u2013Wiener Characterization of Kernels for Finite-Rate-of-Innovation Sampling","display_name":"Paley\u2013Wiener Characterization of Kernels for Finite-Rate-of-Innovation Sampling","publication_year":2017,"publication_date":"2017-07-31","ids":{"openalex":"https://openalex.org/W2739824799","doi":"https://doi.org/10.1109/tsp.2017.2733484","mag":"2739824799"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2017.2733484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2733484","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/A5083205956","display_name":"Satish Mulleti","orcid":"https://orcid.org/0000-0002-3995-9070"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Satish Mulleti","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Science, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005652970","display_name":"Chandra Sekhar Seelamantula","orcid":"https://orcid.org/0000-0001-9049-1912"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chandra Sekhar Seelamantula","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Science, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59270414"],"apc_list":null,"apc_paid":null,"fwci":1.4214,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.7954001,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"65","issue":"22","first_page":"5860","last_page":"5872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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":0.743931770324707},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5749791264533997},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5201778411865234},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5131000280380249},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5018601417541504},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.4905657172203064},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.46958914399147034},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4388194680213928},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4366593360900879},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.4271204173564911},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4224848747253418},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.41514381766319275},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35907724499702454},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2037743628025055},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.18349885940551758},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.15660518407821655}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.743931770324707},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5749791264533997},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5201778411865234},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5131000280380249},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5018601417541504},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.4905657172203064},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.46958914399147034},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4388194680213928},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4366593360900879},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.4271204173564911},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4224848747253418},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.41514381766319275},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35907724499702454},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2037743628025055},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.18349885940551758},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.15660518407821655},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2017.2733484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2733484","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"},{"id":"pmh:oai:eprints.iisc.ac.in:57998","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196309","display_name":"NOT FOUND REPOSITORY (Indian Institute of Science Bangalore)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6700000166893005}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310071","display_name":"Indian Institute of Science","ror":"https://ror.org/04dese585"},{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W71170543","https://openalex.org/W569969529","https://openalex.org/W1508472399","https://openalex.org/W1559478034","https://openalex.org/W1572533413","https://openalex.org/W1624008340","https://openalex.org/W1735999610","https://openalex.org/W1737290388","https://openalex.org/W1945843680","https://openalex.org/W1952629836","https://openalex.org/W1971056102","https://openalex.org/W1979264338","https://openalex.org/W1988588397","https://openalex.org/W1993421475","https://openalex.org/W1997836277","https://openalex.org/W2002663556","https://openalex.org/W2003410902","https://openalex.org/W2035009976","https://openalex.org/W2036268274","https://openalex.org/W2037489965","https://openalex.org/W2038201662","https://openalex.org/W2043422651","https://openalex.org/W2050617763","https://openalex.org/W2052444566","https://openalex.org/W2052867250","https://openalex.org/W2054119616","https://openalex.org/W2055849441","https://openalex.org/W2064314582","https://openalex.org/W2065656021","https://openalex.org/W2071317135","https://openalex.org/W2071966758","https://openalex.org/W2098662489","https://openalex.org/W2099327987","https://openalex.org/W2103217220","https://openalex.org/W2103300762","https://openalex.org/W2103973889","https://openalex.org/W2111273705","https://openalex.org/W2113638573","https://openalex.org/W2118682956","https://openalex.org/W2119876849","https://openalex.org/W2129184388","https://openalex.org/W2136172079","https://openalex.org/W2138787877","https://openalex.org/W2147746039","https://openalex.org/W2152599017","https://openalex.org/W2153058280","https://openalex.org/W2153608957","https://openalex.org/W2158537680","https://openalex.org/W2159028956","https://openalex.org/W2160318164","https://openalex.org/W2166493798","https://openalex.org/W2199507604","https://openalex.org/W2209346800","https://openalex.org/W2243404633","https://openalex.org/W2277164366","https://openalex.org/W2327729044","https://openalex.org/W2408555870","https://openalex.org/W2547849178","https://openalex.org/W2563799792","https://openalex.org/W2732767494","https://openalex.org/W3139866291","https://openalex.org/W3144829920","https://openalex.org/W6659377815","https://openalex.org/W6677814249","https://openalex.org/W6690508466"],"related_works":["https://openalex.org/W1974392290","https://openalex.org/W1911817635","https://openalex.org/W2810224748","https://openalex.org/W2353656796","https://openalex.org/W2011915004","https://openalex.org/W2130974430","https://openalex.org/W3103566292","https://openalex.org/W2074565401","https://openalex.org/W1967187784","https://openalex.org/W1607924090"],"abstract_inverted_index":{"Exact":[0],"reconstruction":[1],"of":[2,83,97,109,143,188,219],"finite-rate-of-innovation":[3],"signals":[4],"can":[5,86],"be":[6],"achieved":[7],"by":[8,197,203],"employing":[9],"customized":[10],"sampling":[11,36,40],"kernels":[12,37,59,90,151],"that":[13,76,94,98,112],"satisfy":[14,60],"certain":[15],"frequency-domain":[16,29],"properties.":[17,68],"We":[18],"impose":[19],"compact":[20],"support":[21,75,93],"in":[22,119,137,154,168,216],"time":[23,121],"as":[24,198,200],"an":[25,141],"additional":[26],"constraint.":[27],"Considering":[28],"reconstruction,":[30],"we":[31,104],"derive":[32],"conditions":[33,63],"for":[34,53,174,182,214],"admissible":[35],"and":[38,64,123,179],"corresponding":[39],"rates.":[41],"Our":[42],"constructive":[43],"kernel":[44,135,208,213],"design":[45],"methodology":[46],"is":[47,77,95,140,170,195],"based":[48],"on":[49],"the":[50,81,88,110,120,129,138,160,166,186,193,211,217],"Paley-Wiener":[51],"theorem":[52],"compactly":[54],"supported":[55],"functions.":[56],"The":[57,132],"new":[58],"generalized":[61],"Strang-Fix":[62],"have":[65,73,91],"specific":[66],"polynomial-modulated-exponential-reproducing":[67],"Unlike":[69],"exponential":[70],"splines,":[71],"which":[72],"a":[74,92,106,114,205],"directly":[78],"proportional":[79],"to":[80,127],"number":[82],"exponentials":[84],"they":[85],"generate,":[87],"proposed":[89],"independent":[96],"number.":[99],"To":[100],"analyze":[101],"noise":[102,130,147],"robustness,":[103],"consider":[105],"special":[107],"member":[108],"class":[111],"has":[113],"sum-of-modulated":[115],"splines":[116],"(SMS)":[117],"form":[118],"domain":[122],"optimize":[124],"its":[125],"parameters":[126],"minimize":[128],"variance.":[131],"sum-of-sincs":[133],"(SoS)":[134],"reported":[136],"literature":[139],"instance":[142],"this":[144],"construction.":[145],"In":[146,163,185],"robustness":[148],"analysis,":[149],"SMS":[150,207],"show":[152],"improvement":[153,167],"mean-squared":[155],"error":[156],"(MSE)":[157],"compared":[158,209],"with":[159,210],"state-of-the-art":[161],"alternatives.":[162],"continuous-time":[164],"noise,":[165,192],"MSE":[169,194],"about":[171],"2":[172],"dB":[173,181,202],"low":[175],"signal-to-noise":[176],"ratio":[177],"(SNR)":[178],"7":[180],"high":[183],"SNR.":[184],"case":[187],"discrete":[189],"white":[190],"Gaussian":[191],"lower":[196],"much":[199],"25":[201],"using":[204],"higher-order":[206],"SoS":[212],"SNRs":[215],"range":[218],"10-15":[220],"dB.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}