{"id":"https://openalex.org/W2972726170","doi":"https://doi.org/10.1109/i2mtc.2019.8826855","title":"Distributed Sampling of Multiple Sinusoids with Finite Rate of Innovation","display_name":"Distributed Sampling of Multiple Sinusoids with Finite Rate of Innovation","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2972726170","doi":"https://doi.org/10.1109/i2mtc.2019.8826855","mag":"2972726170"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc.2019.8826855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2019.8826855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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/A5035426333","display_name":"Zhiliang Wei","orcid":"https://orcid.org/0000-0003-2549-4783"},"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":true,"raw_author_name":"Zhiliang Wei","raw_affiliation_strings":["School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, P.R.China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, P.R.China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025061441","display_name":"Ning Fu","orcid":"https://orcid.org/0000-0002-0317-9697"},"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":"Ning Fu","raw_affiliation_strings":["School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, P.R.China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, P.R.China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006333473","display_name":"Liyan Qiao","orcid":"https://orcid.org/0000-0002-7397-3458"},"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":"Liyan Qiao","raw_affiliation_strings":["School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, P.R.China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, P.R.China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035426333"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.3783,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59325407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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":0.9995999932289124,"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/sampling","display_name":"Sampling (signal processing)","score":0.7532017230987549},{"id":"https://openalex.org/keywords/nyquist\u2013shannon-sampling-theorem","display_name":"Nyquist\u2013Shannon sampling theorem","score":0.699725329875946},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6721652746200562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6554996967315674},{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.5907925963401794},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5836828947067261},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4616381824016571},{"id":"https://openalex.org/keywords/sampling-interval","display_name":"Sampling interval","score":0.4198421239852905},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.41706719994544983},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.38341695070266724},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.267936646938324},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19912588596343994},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.18371975421905518}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7532017230987549},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.699725329875946},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6721652746200562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6554996967315674},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.5907925963401794},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5836828947067261},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4616381824016571},{"id":"https://openalex.org/C2986012078","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling interval","level":2,"score":0.4198421239852905},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.41706719994544983},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.38341695070266724},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.267936646938324},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19912588596343994},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.18371975421905518},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc.2019.8826855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2019.8826855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1564812694","https://openalex.org/W1575298955","https://openalex.org/W1947282229","https://openalex.org/W2003157621","https://openalex.org/W2012376428","https://openalex.org/W2042069995","https://openalex.org/W2052641708","https://openalex.org/W2075433822","https://openalex.org/W2105611770","https://openalex.org/W2111926622","https://openalex.org/W2116627212","https://openalex.org/W2130393104","https://openalex.org/W2149551443","https://openalex.org/W2156454795","https://openalex.org/W2164390589","https://openalex.org/W2165401730","https://openalex.org/W2166500461","https://openalex.org/W2530510227","https://openalex.org/W2573523041","https://openalex.org/W2594151784","https://openalex.org/W2736019836","https://openalex.org/W2787158728","https://openalex.org/W2790255587","https://openalex.org/W2850713931","https://openalex.org/W2889201621"],"related_works":["https://openalex.org/W2368043784","https://openalex.org/W2576230203","https://openalex.org/W3015557210","https://openalex.org/W2009568739","https://openalex.org/W1570358496","https://openalex.org/W2210983845","https://openalex.org/W2119667497","https://openalex.org/W2103898286","https://openalex.org/W2112578300","https://openalex.org/W2393783098"],"abstract_inverted_index":{"In":[0,78],"this":[1],"paper,":[2],"we":[3,35],"propose":[4,46],"a":[5,47,110],"new":[6],"distributed":[7,48],"sampling":[8,24,50,90,112],"scheme":[9],"for":[10,22,66],"multiple":[11,106],"sinusoids":[12,107],"signals,":[13],"which":[14,53],"can":[15,102],"further":[16],"reduce":[17],"the":[18,28,37,67,80,88,93,99,105],"number":[19],"of":[20],"samples":[21,40,59,65],"each":[23],"channel.":[25],"Based":[26],"on":[27],"frequency":[29,73],"sparse":[30],"common":[31],"support":[32],"(SCS)":[33],"model,":[34],"recover":[36,104],"signals":[38,108],"using":[39],"from":[41],"several":[42],"channels":[43],"jointly.":[44],"We":[45],"time-staggered":[49],"(DTSS)":[51],"system,":[52],"requires":[54],"only":[55],"\u0393K":[56],"+":[57],"K/Pl":[58],"per":[60],"non-delay":[61],"channel":[62,69],"and":[63],"K":[64,72],"delay":[68],"when":[70],"recovering":[71],"components":[74],"by":[75],"P":[76],"channels.":[77],"addition,":[79],"staggered":[81],"time":[82],"is":[83],"required":[84],"no":[85],"longer":[86],"than":[87],"Nyquist":[89],"interval":[91],"in":[92],"method.":[94],"Simulation":[95],"results":[96],"verify":[97],"that":[98],"proposed":[100],"methods":[101],"successfully":[103],"at":[109],"lower":[111],"rate.":[113]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
