{"id":"https://openalex.org/W2155059216","doi":"https://doi.org/10.1109/isspa.2010.5605594","title":"A segmented iterative approach to estimation of the coherence spectrum from unevenly sampled sequences","display_name":"A segmented iterative approach to estimation of the coherence spectrum from unevenly sampled sequences","publication_year":2010,"publication_date":"2010-05-01","ids":{"openalex":"https://openalex.org/W2155059216","doi":"https://doi.org/10.1109/isspa.2010.5605594","mag":"2155059216"},"language":"en","primary_location":{"id":"doi:10.1109/isspa.2010.5605594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2010.5605594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5023005411","display_name":"Naveed R. Butt","orcid":"https://orcid.org/0000-0002-6278-2349"},"institutions":[{"id":"https://openalex.org/I187531555","display_name":"Lund University","ror":"https://ror.org/012a77v79","country_code":"SE","type":"education","lineage":["https://openalex.org/I187531555"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Naveed R. Butt","raw_affiliation_strings":["Center for Mathematical Sciences, Lund University, SE-22100, Sweden","Center for Mathematical Sciences, Lund University, Lund, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Mathematical Sciences, Lund University, SE-22100, Sweden","institution_ids":["https://openalex.org/I187531555"]},{"raw_affiliation_string":"Center for Mathematical Sciences, Lund University, Lund, Sweden","institution_ids":["https://openalex.org/I187531555"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037213595","display_name":"Andreas Jakobsson","orcid":"https://orcid.org/0000-0002-2156-6973"},"institutions":[{"id":"https://openalex.org/I187531555","display_name":"Lund University","ror":"https://ror.org/012a77v79","country_code":"SE","type":"education","lineage":["https://openalex.org/I187531555"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Andreas Jakobsson","raw_affiliation_strings":["Center for Mathematical Sciences, Lund University, SE-22100, Sweden","Center for Mathematical Sciences, Lund University, Lund, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Mathematical Sciences, Lund University, SE-22100, Sweden","institution_ids":["https://openalex.org/I187531555"]},{"raw_affiliation_string":"Center for Mathematical Sciences, Lund University, Lund, Sweden","institution_ids":["https://openalex.org/I187531555"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I187531555"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27725978,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"542","last_page":"545"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9983000159263611,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/estimator","display_name":"Estimator","score":0.8228766918182373},{"id":"https://openalex.org/keywords/capon","display_name":"Capon","score":0.7953575849533081},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6244179010391235},{"id":"https://openalex.org/keywords/minimum-variance-unbiased-estimator","display_name":"Minimum-variance unbiased estimator","score":0.5543114542961121},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5220168232917786},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.45765790343284607},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.44770458340644836},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4261268675327301},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38654112815856934},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.11168909072875977}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8228766918182373},{"id":"https://openalex.org/C2778955098","wikidata":"https://www.wikidata.org/wiki/Q594676","display_name":"Capon","level":3,"score":0.7953575849533081},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6244179010391235},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.5543114542961121},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5220168232917786},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.45765790343284607},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.44770458340644836},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4261268675327301},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38654112815856934},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.11168909072875977}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isspa.2010.5605594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2010.5605594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010)","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":22,"referenced_works":["https://openalex.org/W210359992","https://openalex.org/W1506602547","https://openalex.org/W1986027226","https://openalex.org/W1986316936","https://openalex.org/W2012439640","https://openalex.org/W2017464775","https://openalex.org/W2068242608","https://openalex.org/W2077786801","https://openalex.org/W2086972503","https://openalex.org/W2096912514","https://openalex.org/W2112855412","https://openalex.org/W2115891560","https://openalex.org/W2124767781","https://openalex.org/W2140539832","https://openalex.org/W2143716001","https://openalex.org/W2151246884","https://openalex.org/W2153567056","https://openalex.org/W2156267802","https://openalex.org/W2169749822","https://openalex.org/W4249610051","https://openalex.org/W6608552955","https://openalex.org/W6630272163"],"related_works":["https://openalex.org/W2120254062","https://openalex.org/W1553205203","https://openalex.org/W2007634459","https://openalex.org/W3125536267","https://openalex.org/W3168282703","https://openalex.org/W2274645452","https://openalex.org/W1999706086","https://openalex.org/W2521753262","https://openalex.org/W2356451205","https://openalex.org/W1990624027"],"abstract_inverted_index":{"We":[0],"develop":[1],"a":[2,12,78],"non-parametric":[3],"Capon-based":[4,79],"magnitude":[5],"squared":[6],"coherence":[7],"(MSC)":[8],"estimator":[9,54,81,92],"that":[10],"utilizes":[11],"segmented":[13],"reformulation":[14],"of":[15,62,68],"the":[16,63,69,102],"recently":[17],"introduced":[18],"iterative":[19],"adaptive":[20],"approach":[21],"(IAA)":[22],"to":[23,58,83,95,101],"provide":[24],"high":[25],"resolution":[26],"MSC":[27,80,112],"spectrum":[28],"estimates.":[29],"The":[30,53,89],"proposed":[31,90],"estimator,":[32],"termed":[33],"segmented-IAA-MSC":[34],"(or":[35],"SIAA-MSC,":[36],"for":[37,40,47,85],"short),":[38],"allows":[39],"unevenly":[41],"sampled":[42,87],"data":[43],"as":[44,46,99],"well":[45],"sequences":[48],"with":[49],"arbitrarily":[50],"missing":[51],"samples.":[52],"first":[55],"uses":[56],"segmented-IAA":[57],"find":[59],"accurate":[60],"estimates":[61,73,98],"auto-":[64],"and":[65],"cross-covariance":[66],"matrices":[67],"given":[70],"sequences.":[71,88],"These":[72],"are":[74],"then":[75],"used":[76,105],"in":[77],"reformulated":[82],"allow":[84],"non-uniformly":[86],"SIAA-MSC":[91],"is":[93],"found":[94],"yield":[96],"improved":[97],"compared":[100],"more":[103],"commonly":[104],"least":[106],"squares":[107],"Fourier":[108],"transform":[109],"(LSFT)":[110],"based":[111],"estimator.":[113]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
