{"id":"https://openalex.org/W3013237322","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048856","title":"Adaptive Feedback Cancellation for Hearing Aids Using the Prediction-Error Method with Orthonormal Basis Functions","display_name":"Adaptive Feedback Cancellation for Hearing Aids Using the Prediction-Error Method with Orthonormal Basis Functions","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3013237322","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048856","mag":"3013237322"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf44664.2019.9048856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","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/A5045333208","display_name":"Sahar Hashemgeloogerdi","orcid":"https://orcid.org/0000-0001-7352-7864"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sahar Hashemgeloogerdi","raw_affiliation_strings":["University of Rochester, Rochester, NY"],"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026373346","display_name":"Mark F. Bocko","orcid":"https://orcid.org/0000-0002-4768-4660"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark F. Bocko","raw_affiliation_strings":["University of Rochester, Rochester, NY"],"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY","institution_ids":["https://openalex.org/I5388228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045333208"],"corresponding_institution_ids":["https://openalex.org/I5388228"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22301066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"128","last_page":"132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering 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/T11233","display_name":"Advanced Adaptive Filtering 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/T10860","display_name":"Speech and Audio Processing","score":0.9993000030517578,"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.653478741645813},{"id":"https://openalex.org/keywords/orthonormal-basis","display_name":"Orthonormal basis","score":0.5936025977134705},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.570064902305603},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5622485280036926},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.5380124449729919},{"id":"https://openalex.org/keywords/loudspeaker","display_name":"Loudspeaker","score":0.5371025800704956},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5354896187782288},{"id":"https://openalex.org/keywords/recursive-least-squares-filter","display_name":"Recursive least squares filter","score":0.4989006519317627},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.47888487577438354},{"id":"https://openalex.org/keywords/kernel-adaptive-filter","display_name":"Kernel adaptive filter","score":0.4703940153121948},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4486727714538574},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.44566547870635986},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3964478373527527},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30331748723983765},{"id":"https://openalex.org/keywords/filter-design","display_name":"Filter design","score":0.29453152418136597},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14014559984207153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11515504121780396},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09455883502960205}],"concepts":[{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.653478741645813},{"id":"https://openalex.org/C5806529","wikidata":"https://www.wikidata.org/wiki/Q2365325","display_name":"Orthonormal basis","level":2,"score":0.5936025977134705},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.570064902305603},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5622485280036926},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.5380124449729919},{"id":"https://openalex.org/C157138929","wikidata":"https://www.wikidata.org/wiki/Q570","display_name":"Loudspeaker","level":2,"score":0.5371025800704956},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5354896187782288},{"id":"https://openalex.org/C145249878","wikidata":"https://www.wikidata.org/wiki/Q2835868","display_name":"Recursive least squares filter","level":3,"score":0.4989006519317627},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.47888487577438354},{"id":"https://openalex.org/C13107197","wikidata":"https://www.wikidata.org/wiki/Q6394192","display_name":"Kernel adaptive filter","level":4,"score":0.4703940153121948},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4486727714538574},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.44566547870635986},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3964478373527527},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30331748723983765},{"id":"https://openalex.org/C22597639","wikidata":"https://www.wikidata.org/wiki/Q5449227","display_name":"Filter design","level":3,"score":0.29453152418136597},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14014559984207153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11515504121780396},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09455883502960205},{"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/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ieeeconf44664.2019.9048856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"},{"id":"mag:3042837547","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002221277087909","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W292716351","https://openalex.org/W608300865","https://openalex.org/W1654142233","https://openalex.org/W1977144816","https://openalex.org/W1980638739","https://openalex.org/W2025322216","https://openalex.org/W2036512040","https://openalex.org/W2056678683","https://openalex.org/W2097095546","https://openalex.org/W2140828385","https://openalex.org/W2148862269","https://openalex.org/W2151141216","https://openalex.org/W2156367112","https://openalex.org/W2158760189","https://openalex.org/W2346509311","https://openalex.org/W2634512046","https://openalex.org/W2759873418","https://openalex.org/W2770442457","https://openalex.org/W2781397332","https://openalex.org/W2786581051","https://openalex.org/W2885818641","https://openalex.org/W2973841804","https://openalex.org/W6645171280","https://openalex.org/W6739571675"],"related_works":["https://openalex.org/W2556507952","https://openalex.org/W4282823030","https://openalex.org/W2567448372","https://openalex.org/W2164852895","https://openalex.org/W3119704784","https://openalex.org/W2529395309","https://openalex.org/W1976772112","https://openalex.org/W2100442903","https://openalex.org/W1858111639","https://openalex.org/W4380628797"],"abstract_inverted_index":{"Hearing":[0],"aids":[1],"are":[2,148],"susceptible":[3],"to":[4,55,73,112,182],"acoustic":[5],"feedback,":[6],"which":[7],"limits":[8],"the":[9,16,32,43,52,58,75,89,94,107,114,124,159,169,173,179,183],"achievable":[10],"amplification":[11],"and":[12,60,92,123,142,156,176],"may":[13],"severely":[14],"degrade":[15],"sound":[17],"quality":[18],"by":[19,136],"producing":[20],"howling":[21],"artifacts.":[22],"A":[23,63],"potential":[24],"method":[25,65,103,155,171],"of":[26,31,42,84,120,139],"feedback":[27,33],"cancellation":[28],"employs":[29],"prediction":[30],"path":[34],"(FP)":[35],"with":[36,116],"an":[37,128,151],"adaptive":[38,85,121,143,190],"filter.":[39],"However,":[40,77],"estimation":[41],"FP":[44,115],"suffers":[45],"a":[46,81,101,117,137,162],"large":[47,82],"model":[48],"error,":[49],"known":[50],"as":[51,161],"bias,":[53],"due":[54],"correlation":[56],"between":[57],"loudspeaker":[59],"source":[61,125],"signals.":[62],"prediction-error":[64],"(PEM)":[66],"based":[67,105],"pre-whitening":[68],"filter":[69,133,160],"has":[70],"been":[71],"utilized":[72],"reduce":[74],"bias.":[76],"this":[78],"approach":[79],"requires":[80],"number":[83,119],"parameters,":[86],"thus":[87],"reducing":[88],"convergence":[90,174],"rate":[91,175],"limiting":[93],"added":[95],"stable":[96,153],"gain":[97],"(ASG).":[98],"We":[99],"introduce":[100],"PEM-based":[102],"derived":[104],"upon":[106],"orthonormal":[108],"basis":[109],"functions":[110],"(OBFs)":[111],"estimate":[113],"small":[118],"parameters":[122],"signal":[126],"using":[127,150],"autoregressive":[129],"model.":[130],"The":[131,146],"OBF":[132],"is":[134],"defined":[135],"set":[138],"fixed":[140],"poles":[141,147],"tap-output":[144],"weights.":[145],"estimated":[149],"inherently":[152],"least-squares":[154],"embedded":[157],"into":[158],"priori":[163],"information.":[164],"Experimental":[165],"results":[166],"show":[167],"that":[168],"proposed":[170],"enhances":[172],"significantly":[177],"increases":[178],"ASG":[180],"compared":[181],"standard":[184],"PEM,":[185],"while":[186],"uses":[187],"far":[188],"fewer":[189],"parameters.":[191]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}