{"id":"https://openalex.org/W2902683700","doi":"https://doi.org/10.23919/eusipco.2018.8553470","title":"Sampling a Noisy Multiple Output Channel to Maximize the Capacity","display_name":"Sampling a Noisy Multiple Output Channel to Maximize the Capacity","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2902683700","doi":"https://doi.org/10.23919/eusipco.2018.8553470","mag":"2902683700"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553470","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","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/A5086640652","display_name":"Gaston Solodky","orcid":"https://orcid.org/0000-0003-2311-2956"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Gaston Solodky","raw_affiliation_strings":["School of Electrical Engineering, Tel Aviv University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Tel Aviv University","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066905280","display_name":"Meir Feder","orcid":"https://orcid.org/0000-0002-1290-0482"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Meir Feder","raw_affiliation_strings":["School of Electrical Engineering, Tel Aviv University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Tel Aviv University","institution_ids":["https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5086640652"],"corresponding_institution_ids":["https://openalex.org/I16391192"],"apc_list":null,"apc_paid":null,"fwci":1.3724,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80114932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"445","last_page":"449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.9991999864578247,"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":0.9991999864578247,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9990000128746033,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.998199999332428,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.8408305644989014},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6635560989379883},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.615690290927887},{"id":"https://openalex.org/keywords/nyquist\u2013shannon-sampling-theorem","display_name":"Nyquist\u2013Shannon sampling theorem","score":0.573409914970398},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.4987502098083496},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4985175132751465},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4930116832256317},{"id":"https://openalex.org/keywords/channel-capacity","display_name":"Channel capacity","score":0.4867260754108429},{"id":"https://openalex.org/keywords/nyquist-frequency","display_name":"Nyquist frequency","score":0.45377641916275024},{"id":"https://openalex.org/keywords/lti-system-theory","display_name":"LTI system theory","score":0.4234233498573303},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4226689338684082},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39645877480506897},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.38040778040885925},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.32838159799575806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.27899959683418274},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.19874000549316406},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16128811240196228},{"id":"https://openalex.org/keywords/linear-system","display_name":"Linear system","score":0.15696638822555542},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.07870885729789734}],"concepts":[{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.8408305644989014},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6635560989379883},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.615690290927887},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.573409914970398},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.4987502098083496},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4985175132751465},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4930116832256317},{"id":"https://openalex.org/C97744766","wikidata":"https://www.wikidata.org/wiki/Q870845","display_name":"Channel capacity","level":3,"score":0.4867260754108429},{"id":"https://openalex.org/C98273374","wikidata":"https://www.wikidata.org/wiki/Q1501757","display_name":"Nyquist frequency","level":3,"score":0.45377641916275024},{"id":"https://openalex.org/C87698059","wikidata":"https://www.wikidata.org/wiki/Q1808960","display_name":"LTI system theory","level":3,"score":0.4234233498573303},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4226689338684082},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39645877480506897},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.38040778040885925},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32838159799575806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.27899959683418274},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.19874000549316406},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16128811240196228},{"id":"https://openalex.org/C6802819","wikidata":"https://www.wikidata.org/wiki/Q1072174","display_name":"Linear system","level":2,"score":0.15696638822555542},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.07870885729789734},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2018.8553470","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W649866511","https://openalex.org/W1988588397","https://openalex.org/W1989008275","https://openalex.org/W2130509920","https://openalex.org/W2142901448","https://openalex.org/W2152849921","https://openalex.org/W2155092009","https://openalex.org/W2902683700"],"related_works":["https://openalex.org/W2368043784","https://openalex.org/W1500996803","https://openalex.org/W2058893726","https://openalex.org/W2801332561","https://openalex.org/W3215214094","https://openalex.org/W1488455774","https://openalex.org/W1570358496","https://openalex.org/W2124861257","https://openalex.org/W3015557210","https://openalex.org/W3128645236"],"abstract_inverted_index":{"This":[0],"paper":[1],"deals":[2],"with":[3,69],"an":[4,119,146],"extension":[5],"of":[6,44,63,152],"Papoulis'":[7],"generalized":[8],"sampling":[9,20,24,38,132,141,160],"expansion":[10],"(GSE)":[11],"to":[12],"a":[13,158],"case":[14,76],"where":[15,58,77,143],"noise":[16],"is":[17,81,133,145],"added":[18],"before":[19],"and":[21,52,84,99,154,174],"the":[22,30,36,42,45,49,53,59,75,78,87,90,100,104,111,127,150,155,162,168,172,176],"total":[23,79,140,156],"rate":[25,80,98],"may":[26],"be":[27,116],"higher":[28],"than":[29],"Nyquist":[31,88,97],"rate.":[32,106],"We":[33],"look":[34],"for":[35,138],"best":[37],"scheme":[39,92,122],"that":[40],"maximizes":[41],"capacity":[43,173],"sampled":[46,55,121],"channel":[47],"between":[48,82,149,170],"input":[50],"signal":[51],"M":[54,85,108],"outputs":[56,95],"signals,":[57],"channels":[60,153],"are":[61],"composed":[62],"all-pass":[64],"linear":[65],"time-invariant":[66],"(LTI)":[67],"systems":[68],"additive":[70],"Gaussian":[71],"white":[72],"noise.":[73],"For":[74],"M-1":[83,94],"times":[86],"rate,":[89,157],"optimal":[91,112,163],"samples":[93],"at":[96,103],"last":[101],"output":[102],"remaining":[105],"When":[107],"=":[109],"2":[110],"performance":[113],"can":[114],"also":[115],"attained":[117],"by":[118],"equally":[120],"under":[123],"some":[124,139],"condition":[125],"on":[126],"LTI":[128],"systems.":[129],"Surprisingly,":[130],"equal":[131],"suboptimal":[134],"in":[135],"general.":[136],"Nevertheless,":[137],"rates":[142],"there":[144],"integer":[147],"relation":[148,169],"number":[151],"uniform":[159],"achieves":[161],"performance.":[164],"Finally,":[165],"we":[166],"discuss":[167],"maximizing":[171],"minimizing":[175],"mean-square":[177],"error.":[178]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"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"}