{"id":"https://openalex.org/W2117745665","doi":"https://doi.org/10.1109/icassp.1985.1168342","title":"Detection algorithms based on prediction error - additive noise - data orthogonality","display_name":"Detection algorithms based on prediction error - additive noise - data orthogonality","publication_year":2005,"publication_date":"2005-03-23","ids":{"openalex":"https://openalex.org/W2117745665","doi":"https://doi.org/10.1109/icassp.1985.1168342","mag":"2117745665"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1985.1168342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","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/A5085868377","display_name":"M.K. Ibrahim","orcid":"https://orcid.org/0009-0006-8054-4287"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"M. Ibrahim","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Newcastle, UK"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Newcastle, UK","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112615786","display_name":"C.E. Goutis","orcid":null},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"C. Goutis","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Newcastle, UK"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Newcastle, UK","institution_ids":["https://openalex.org/I84884186"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085868377"],"corresponding_institution_ids":["https://openalex.org/I84884186"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25734066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"644","last_page":"647"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9968000054359436,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.7127748727798462},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6617057919502258},{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.6451314687728882},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6150128841400146},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5834752321243286},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5050082802772522},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.504334568977356},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4969015419483185},{"id":"https://openalex.org/keywords/covariance-intersection","display_name":"Covariance intersection","score":0.4706118702888489},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.42322802543640137},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.4169883728027344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40223824977874756},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.25618070363998413},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1691044270992279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.167679101228714}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7127748727798462},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6617057919502258},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.6451314687728882},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6150128841400146},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5834752321243286},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5050082802772522},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.504334568977356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4969015419483185},{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.4706118702888489},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.42322802543640137},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.4169883728027344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40223824977874756},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.25618070363998413},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1691044270992279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.167679101228714},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1985.1168342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","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":7,"referenced_works":["https://openalex.org/W2031887434","https://openalex.org/W2045371436","https://openalex.org/W2068392125","https://openalex.org/W2134392874","https://openalex.org/W2162443378","https://openalex.org/W2326591006","https://openalex.org/W4247757348"],"related_works":["https://openalex.org/W2144859729","https://openalex.org/W2401337578","https://openalex.org/W3084622875","https://openalex.org/W2572601863","https://openalex.org/W2118568436","https://openalex.org/W2018001152","https://openalex.org/W4224918813","https://openalex.org/W1974588588","https://openalex.org/W1489099099","https://openalex.org/W2109377650"],"abstract_inverted_index":{"Two":[0],"new":[1],"iterative":[2],"algorithms":[3],"for":[4,80],"AR":[5,39,78],"parameter":[6],"estimation":[7],"are":[8,44],"presented.":[9],"The":[10,50],"first":[11],"minimizes":[12,53],"the":[13,16,21,32,54,58,62,77,81,88],"sum":[14],"of":[15,76],"prediction":[17,25,59],"error":[18,26,60],"energy":[19],"and":[20,27,30,61,74],"cross":[22,55],"covariance":[23,34,56],"between":[24,57],"additive":[28],"noise,":[29],"models":[31],"noise":[33],"matrix":[35],"with":[36],"a":[37,67],"separate":[38],"filter":[40,79],"whose":[41],"reflection":[42,90],"coefficient":[43],"constrained":[45],"to":[46,92],"be":[47,93],"sufficiently":[48],"small.":[49],"second":[51],"algorithm":[52,66],"data.":[63],"In":[64],"both":[65],"steepest":[68],"descent":[69],"updating":[70],"procedure":[71],"is":[72,84],"employed":[73],"stability":[75],"stohastic":[82],"processes":[83],"ensured":[85],"by":[86],"constraining":[87],"corresponding":[89],"coefficients":[91],"less":[94],"than":[95],"one.":[96]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}