{"id":"https://openalex.org/W2139670521","doi":"https://doi.org/10.1109/icassp.2005.1415958","title":"An Approach to ARMA System Identification at a Very Low Signal-To-Noise Ratio","display_name":"An Approach to ARMA System Identification at a Very Low Signal-To-Noise Ratio","publication_year":2006,"publication_date":"2006-10-11","ids":{"openalex":"https://openalex.org/W2139670521","doi":"https://doi.org/10.1109/icassp.2005.1415958","mag":"2139670521"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2005.1415958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.","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/A5074606314","display_name":"Shaikh Anowarul Fattah","orcid":"https://orcid.org/0000-0001-8090-2327"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaikh Anowarul Fattah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033247734","display_name":"Wei\u2010Ping Zhu","orcid":"https://orcid.org/0000-0001-7955-7044"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"W.-P. Zhu","raw_affiliation_strings":["Centre for Signal Processing and Communications, Department of Electrical and Computer Engineering, Concordia University, Montreal, QUE, Canada","Dept. of Electr. & Comput. Eng. Concordia Univ., Montreal, Que., Canada#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Signal Processing and Communications, Department of Electrical and Computer Engineering, Concordia University, Montreal, QUE, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng. Concordia Univ., Montreal, Que., Canada#TAB#","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068820891","display_name":"M. Omair Ahmad","orcid":"https://orcid.org/0000-0002-2924-6659"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M. Omair Ahmad","raw_affiliation_strings":["Centre for Signal Processing and Communications, Department of Electrical and Computer Engineering, Concordia University, Montreal, QUE, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Signal Processing and Communications, Department of Electrical and Computer Engineering, Concordia University, Montreal, QUE, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2635,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.8810547,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"4","issue":null,"first_page":"113","last_page":"116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"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":0.9980000257492065,"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/T10860","display_name":"Speech and Audio Processing","score":0.9965999722480774,"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/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.7786502838134766},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.7658262252807617},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7291793823242188},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.6220167875289917},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5752562284469604},{"id":"https://openalex.org/keywords/impulse-response","display_name":"Impulse response","score":0.5441209077835083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5105754137039185},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5065418481826782},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.49193286895751953},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4788132309913635},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.4554150104522705},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4207199811935425},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4090760350227356},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3544856607913971},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3201349377632141},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2878677248954773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1730227768421173},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.15820497274398804},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.1092829704284668}],"concepts":[{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.7786502838134766},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.7658262252807617},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7291793823242188},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.6220167875289917},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5752562284469604},{"id":"https://openalex.org/C72279823","wikidata":"https://www.wikidata.org/wiki/Q1139726","display_name":"Impulse response","level":2,"score":0.5441209077835083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5105754137039185},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5065418481826782},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.49193286895751953},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4788132309913635},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.4554150104522705},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4207199811935425},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4090760350227356},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3544856607913971},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3201349377632141},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2878677248954773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1730227768421173},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.15820497274398804},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.1092829704284668},{"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"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/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2005.1415958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1512197373","https://openalex.org/W1597732836","https://openalex.org/W2042094536","https://openalex.org/W2088310696","https://openalex.org/W2124735774","https://openalex.org/W2136612776","https://openalex.org/W2159379282","https://openalex.org/W2169851606","https://openalex.org/W2485688913","https://openalex.org/W6630658681"],"related_works":["https://openalex.org/W2036994430","https://openalex.org/W1624875519","https://openalex.org/W2413726729","https://openalex.org/W3190289737","https://openalex.org/W1985666753","https://openalex.org/W2071448233","https://openalex.org/W2384744720","https://openalex.org/W1580508919","https://openalex.org/W2367697829","https://openalex.org/W2364898010"],"abstract_inverted_index":{"A":[0,24],"new":[1],"approach":[2],"for":[3,29,101,143],"the":[4,14,30,42,47,56,74,102,105,147],"identification":[5,110,134],"of":[6,16,33,49,59,73,104,140,146],"minimum-phase":[7],"autoregressive":[8],"moving":[9],"average":[10],"(ARMA)":[11],"systems":[12,127],"in":[13,21,54],"presence":[15],"heavy":[17],"noise":[18,93],"is":[19,38],"presented":[20],"this":[22],"paper.":[23],"damped":[25],"sinusoidal":[26],"(DS)":[27],"model":[28],"autocorrelation":[31],"function":[32],"a":[34,64],"noise-free":[35],"ARMA":[36,61,75,126],"signal":[37],"proposed":[39,106],"to":[40,108,114],"estimate":[41],"AR":[43,57],"parameters,":[44],"which":[45,144],"overcomes":[46],"failure":[48],"conventional":[50],"correlation":[51],"based":[52,122],"techniques":[53],"estimating":[55],"parameters":[58,72],"an":[60,86,138],"system":[62,76,109],"at":[63,137],"very":[65],"low":[66],"signal-to-noise":[67],"ratio":[68],"(SNR).":[69],"The":[70],"MA":[71],"are":[77,99,119],"then":[78],"estimated":[79],"by":[80],"using":[81],"Durbin's":[82],"method":[83,107],"along":[84],"with":[85],"optimum":[87],"order":[88],"selection":[89],"criterion.":[90],"Both":[91],"white":[92],"and":[94,128],"periodic":[95],"impulse":[96],"train":[97],"excitations":[98],"considered":[100],"application":[103],"as":[111,113],"well":[112],"speech":[115,130],"processing.":[116],"Computer":[117],"simulations":[118],"carried":[120],"out":[121],"on":[123],"both":[124],"synthetic":[125],"natural":[129],"signals,":[131],"showing":[132],"superior":[133],"results":[135],"even":[136],"SNR":[139],"-5":[141],"dB":[142],"most":[145],"existing":[148],"methods":[149],"would":[150],"fail.":[151]},"counts_by_year":[{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
