{"id":"https://openalex.org/W4392902902","doi":"https://doi.org/10.1109/icassp48485.2024.10447003","title":"Frequency Estimation via Sub-Nyquist Unlimited Sampling","display_name":"Frequency Estimation via Sub-Nyquist Unlimited Sampling","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392902902","doi":"https://doi.org/10.1109/icassp48485.2024.10447003"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5100646472","display_name":"Yuliang Zhu","orcid":"https://orcid.org/0000-0003-3987-9908"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yuliang Zhu","raw_affiliation_strings":["Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027325710","display_name":"Ruiming Guo","orcid":"https://orcid.org/0000-0002-9449-4042"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ruiming Guo","raw_affiliation_strings":["Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605328","display_name":"Peiyu Zhang","orcid":"https://orcid.org/0000-0002-9773-0514"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peiyu Zhang","raw_affiliation_strings":["Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029074414","display_name":"Ayush Bhandari","orcid":"https://orcid.org/0000-0002-4485-2569"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ayush Bhandari","raw_affiliation_strings":["Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College,Dept. of Electrical and Electronic Engg.,London,UK,SW7 2AZ","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":3.8492,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.93926209,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"9636","last_page":"9640"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9991000294685364,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/oversampling","display_name":"Oversampling","score":0.8890912532806396},{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.7791226506233215},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7515637874603271},{"id":"https://openalex.org/keywords/nyquist\u2013shannon-sampling-theorem","display_name":"Nyquist\u2013Shannon sampling theorem","score":0.7218190431594849},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6761203408241272},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5530354976654053},{"id":"https://openalex.org/keywords/nyquist-frequency","display_name":"Nyquist frequency","score":0.5504839420318604},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.49194976687431335},{"id":"https://openalex.org/keywords/converters","display_name":"Converters","score":0.4615820050239563},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.4242740869522095},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.423789381980896},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3499391973018646},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.2228013575077057},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12122005224227905},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10702943801879883},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.07907167077064514},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07774803042411804}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.8890912532806396},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.7791226506233215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7515637874603271},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.7218190431594849},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6761203408241272},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5530354976654053},{"id":"https://openalex.org/C98273374","wikidata":"https://www.wikidata.org/wiki/Q1501757","display_name":"Nyquist frequency","level":3,"score":0.5504839420318604},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.49194976687431335},{"id":"https://openalex.org/C2778422915","wikidata":"https://www.wikidata.org/wiki/Q10302051","display_name":"Converters","level":3,"score":0.4615820050239563},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.4242740869522095},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.423789381980896},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3499391973018646},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.2228013575077057},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12122005224227905},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10702943801879883},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.07907167077064514},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07774803042411804},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1979090482","https://openalex.org/W2020504273","https://openalex.org/W2066147577","https://openalex.org/W2126153569","https://openalex.org/W2164390589","https://openalex.org/W2286274660","https://openalex.org/W2511048156","https://openalex.org/W2737827235","https://openalex.org/W2790255587","https://openalex.org/W2801332561","https://openalex.org/W2886711647","https://openalex.org/W2944333051","https://openalex.org/W3105381059","https://openalex.org/W3198071097","https://openalex.org/W3199048522","https://openalex.org/W3217376978","https://openalex.org/W4214871684","https://openalex.org/W4221017392","https://openalex.org/W4372346848","https://openalex.org/W4372347437","https://openalex.org/W4375868808","https://openalex.org/W4385834398"],"related_works":["https://openalex.org/W2103898286","https://openalex.org/W3135590747","https://openalex.org/W2368043784","https://openalex.org/W1500996803","https://openalex.org/W4242173009","https://openalex.org/W2981337968","https://openalex.org/W2963311259","https://openalex.org/W2056235298","https://openalex.org/W1524628891","https://openalex.org/W1488455774"],"abstract_inverted_index":{"The":[0],"problem":[1],"of":[2,26,33,44,67,131,168],"frequency":[3,52,103],"estimation":[4,104],"from":[5,85,105],"sub-Nyquist":[6,69,109],"samples":[7,87,107],"has":[8,15,36],"numerous":[9],"applications":[10],"across":[11],"various":[12],"disciplines":[13],"and":[14,157],"been":[16,38],"extensively":[17],"studied":[18],"in":[19,171],"signal":[20],"processing":[21],"literature.":[22],"Despite":[23],"the":[24,30,42,59,68,75,132,166,180],"existence":[25],"several":[27],"algorithmic":[28],"approaches,":[29],"full":[31],"potential":[32],"these":[34],"methods":[35],"not":[37],"realized":[39],"due":[40],"to":[41],"limitations":[43],"analog-to-digital":[45],"converters":[46],"(ADCs).":[47],"In":[48,91],"particular,":[49],"accurately":[50],"estimating":[51],"for":[53,102,179],"high-dynamic-range":[54],"signals":[55,84],"that":[56,100,115],"may":[57],"saturate":[58],"ADC":[60],"is":[61,114],"still":[62],"an":[63],"interesting":[64],"problem,":[65],"regardless":[66],"aspect.":[70],"On":[71],"a":[72,96,140,147],"different":[73],"note,":[74],"Unlimited":[76],"Sensing":[77],"Framework":[78],"(USF)":[79],"focuses":[80],"on":[81],"recovering":[82],"large":[83],"folded":[86,106],"but":[88],"requires":[89],"oversampling.":[90],"this":[92],"paper,":[93],"we":[94,138,153],"propose":[95],"hardware-software":[97],"co-design":[98],"approach":[99,160],"allows":[101],"at":[108],"rates.":[110],"Our":[111],"key":[112],"insight":[113],"temporal":[116],"redundancy":[117],"can":[118],"be":[119],"eliminated":[120],"by":[121],"introducing":[122],"channel":[123],"redundancy.":[124],"Surprisingly,":[125],"our":[126,159,169],"recovery":[127],"guarantees":[128],"are":[129],"independent":[130],"sampling":[133,143],"rate.":[134],"To":[135],"achieve":[136],"this,":[137],"introduce":[139],"novel":[141],"multi-channel":[142],"pipeline":[144],"coupled":[145],"with":[146],"reconstruction":[148],"algorithm.":[149],"Beyond":[150],"numerical":[151],"experiments,":[152],"build":[154],"customized":[155],"hardware":[156],"validate":[158],"through":[161],"lab":[162],"experiments.":[163],"This":[164],"demonstrates":[165],"capabilities":[167],"method":[170],"real-world":[172],"scenarios":[173],"while":[174],"opening":[175],"up":[176],"new":[177],"questions":[178],"field.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}