{"id":"https://openalex.org/W2989637271","doi":"https://doi.org/10.1109/lsp.2019.2955815","title":"Cross Term Decay in Multiplicative Processors","display_name":"Cross Term Decay in Multiplicative Processors","publication_year":2019,"publication_date":"2019-11-25","ids":{"openalex":"https://openalex.org/W2989637271","doi":"https://doi.org/10.1109/lsp.2019.2955815","mag":"2989637271"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2019.2955815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2955815","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/A5006117118","display_name":"Vaibhav Chavali","orcid":"https://orcid.org/0000-0003-3975-4814"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vaibhav Chavali","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3975-4814","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040405628","display_name":"Kathleen E. Wage","orcid":"https://orcid.org/0000-0002-3412-1885"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kathleen E. Wage","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3412-1885","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57818492,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"27","issue":null,"first_page":"56","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9998000264167786,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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":0.9986000061035156,"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/algorithm","display_name":"Algorithm","score":0.6178867220878601},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5991173386573792},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.5822799801826477},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.47849908471107483},{"id":"https://openalex.org/keywords/cumulative-distribution-function","display_name":"Cumulative distribution function","score":0.47310519218444824},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.46846458315849304},{"id":"https://openalex.org/keywords/tapering","display_name":"Tapering","score":0.46726030111312866},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.4531385004520416},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38072702288627625},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1998041272163391},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19644400477409363},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.14359134435653687},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.134515643119812}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6178867220878601},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5991173386573792},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.5822799801826477},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.47849908471107483},{"id":"https://openalex.org/C103784038","wikidata":"https://www.wikidata.org/wiki/Q386228","display_name":"Cumulative distribution function","level":3,"score":0.47310519218444824},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.46846458315849304},{"id":"https://openalex.org/C114138010","wikidata":"https://www.wikidata.org/wiki/Q7684542","display_name":"Tapering","level":2,"score":0.46726030111312866},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.4531385004520416},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38072702288627625},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1998041272163391},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19644400477409363},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.14359134435653687},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.134515643119812},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2019.2955815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2955815","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":[{"id":"https://openalex.org/G4120331641","display_name":null,"funder_award_id":"N00014-18-1-2669","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G924440650","display_name":null,"funder_award_id":"N00014-17-1-2734","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W639989723","https://openalex.org/W653761051","https://openalex.org/W1515407204","https://openalex.org/W1572529184","https://openalex.org/W1964521756","https://openalex.org/W1978026911","https://openalex.org/W2003157621","https://openalex.org/W2010066971","https://openalex.org/W2013122854","https://openalex.org/W2014828495","https://openalex.org/W2028988082","https://openalex.org/W2036374007","https://openalex.org/W2076393035","https://openalex.org/W2079302539","https://openalex.org/W2098174516","https://openalex.org/W2098835193","https://openalex.org/W2114907259","https://openalex.org/W2144000894","https://openalex.org/W2160468305","https://openalex.org/W2164390589","https://openalex.org/W2286274660","https://openalex.org/W2308717554","https://openalex.org/W2312939532","https://openalex.org/W2335128326","https://openalex.org/W2357400875","https://openalex.org/W2560032208","https://openalex.org/W2580609400","https://openalex.org/W2586607074","https://openalex.org/W2604460297","https://openalex.org/W2618327330","https://openalex.org/W2637565786","https://openalex.org/W2686256227","https://openalex.org/W2742426150","https://openalex.org/W2742609933","https://openalex.org/W2763020411","https://openalex.org/W2765769139","https://openalex.org/W2765842461","https://openalex.org/W2790209414","https://openalex.org/W2808559592","https://openalex.org/W2891218454","https://openalex.org/W2904450801","https://openalex.org/W2909746651","https://openalex.org/W2914623695","https://openalex.org/W2916215870","https://openalex.org/W2941868087","https://openalex.org/W2942508766","https://openalex.org/W2955189360","https://openalex.org/W4211251910","https://openalex.org/W4232369613"],"related_works":["https://openalex.org/W1610290348","https://openalex.org/W2379029750","https://openalex.org/W3036616393","https://openalex.org/W2745181518","https://openalex.org/W4224861938","https://openalex.org/W2359525189","https://openalex.org/W3098561164","https://openalex.org/W2048978945","https://openalex.org/W4298471994","https://openalex.org/W2782824255"],"abstract_inverted_index":{"Multiplicative":[0],"processors":[1],"combine":[2],"the":[3,11,16,24,40,54,67,76,83,95,106,108,115,124,161],"beamformed":[4],"outputs":[5],"of":[6,57,85,97,123,126,128,144,149,163],"undersampled":[7],"subarrays":[8],"to":[9,22,100],"estimate":[10],"spatial":[12],"power":[13],"spectrum.":[14],"While":[15,152],"multiplicative":[17],"processor":[18],"requires":[19],"fewer":[20],"sensors":[21],"achieve":[23],"same":[25],"resolution":[26],"as":[27],"a":[28,50,62,142],"conventional":[29],"linear":[30],"processor,":[31],"it":[32,158],"also":[33,159],"produces":[34],"cross":[35,73,90,138,167],"terms":[36,44,74,139],"that":[37,137],"can":[38],"degrade":[39],"spectral":[41],"estimate.":[42],"Cross":[43],"are":[45,78],"false":[46],"peaks":[47],"formed":[48],"when":[49,75],"signal":[51,64],"passing":[52,65],"through":[53,66],"grating":[55],"lobe":[56],"one":[58],"subarray":[59,98,153],"interacts":[60],"with":[61],"different":[63],"other":[68],"subarray.":[69],"Snapshot":[70],"averaging":[71],"reduces":[72,155],"signals":[77],"uncorrelated.":[79],"This":[80],"letter":[81,109],"quantifies":[82],"number":[84,162],"snapshots":[86,150,164],"required":[87,165],"for":[88,94,114,166],"effective":[89],"term":[91,168],"mitigation,":[92],"accounting":[93],"use":[96],"tapers":[99],"control":[101],"sidelobe":[102,156],"levels.":[103],"To":[104],"facilitate":[105],"analysis,":[107],"derives":[110],"closed":[111],"form":[112],"expressions":[113],"probability":[116],"density":[117],"function":[118,122],"and":[119],"cumulative":[120],"distribution":[121],"sum":[125],"products":[127],"independent":[129],"complex":[130],"Gaussian":[131],"random":[132],"variables.":[133],"The":[134],"analysis":[135],"demonstrates":[136],"decay":[140],"at":[141],"rate":[143],"5":[145],"dB":[146],"per":[147],"decade":[148],"averaged.":[151],"tapering":[154],"leakage,":[157],"increases":[160],"mitigation.":[169]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
