{"id":"https://openalex.org/W1534878676","doi":"https://doi.org/10.1109/glocom.2002.1188087","title":"Adaptive channel equalization using approximate Bayesian criterion","display_name":"Adaptive channel equalization using approximate Bayesian criterion","publication_year":2003,"publication_date":"2003-11-21","ids":{"openalex":"https://openalex.org/W1534878676","doi":"https://doi.org/10.1109/glocom.2002.1188087","mag":"1534878676"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2002.1188087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2002.1188087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE","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/A5115590665","display_name":"Ren-Jr Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ren-Jr Chen","raw_affiliation_strings":["Department of Communication Engineering, National Chiao Tung University, Hsinchu, Taiwan","Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsin Chu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Communication Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]},{"raw_affiliation_string":"Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsin Chu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110247937","display_name":"Wen-Rong Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wen-Rong Wu","raw_affiliation_strings":["Department of Communication Engineering, National Chiao Tung University, Hsinchu, Taiwan","Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsin Chu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Communication Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]},{"raw_affiliation_string":"Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsin Chu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04941543,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"292","last_page":"296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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/T10320","display_name":"Neural Networks and Applications","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computational-complexity-theory","display_name":"Computational complexity theory","score":0.7287477254867554},{"id":"https://openalex.org/keywords/hyperplane","display_name":"Hyperplane","score":0.7154133319854736},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5956931114196777},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5676836371421814},{"id":"https://openalex.org/keywords/adaptive-equalizer","display_name":"Adaptive equalizer","score":0.5179002285003662},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5085164308547974},{"id":"https://openalex.org/keywords/equalization","display_name":"Equalization (audio)","score":0.49146568775177},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.44386595487594604},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43118464946746826},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4207778573036194},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30451852083206177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21774446964263916},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.10729661583900452}],"concepts":[{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.7287477254867554},{"id":"https://openalex.org/C68693459","wikidata":"https://www.wikidata.org/wiki/Q657586","display_name":"Hyperplane","level":2,"score":0.7154133319854736},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5956931114196777},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5676836371421814},{"id":"https://openalex.org/C25125847","wikidata":"https://www.wikidata.org/wiki/Q4680741","display_name":"Adaptive equalizer","level":4,"score":0.5179002285003662},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5085164308547974},{"id":"https://openalex.org/C75755367","wikidata":"https://www.wikidata.org/wiki/Q104531076","display_name":"Equalization (audio)","level":3,"score":0.49146568775177},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.44386595487594604},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43118464946746826},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4207778573036194},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30451852083206177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21774446964263916},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.10729661583900452},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/glocom.2002.1188087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2002.1188087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE","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":0.5299999713897705},{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W88258989","https://openalex.org/W583903863","https://openalex.org/W1940045019","https://openalex.org/W1971052094","https://openalex.org/W2063541597","https://openalex.org/W2085400870","https://openalex.org/W2104893535","https://openalex.org/W2109610566","https://openalex.org/W2116952199","https://openalex.org/W2153204558","https://openalex.org/W2163382639","https://openalex.org/W3144557800","https://openalex.org/W6677300854"],"related_works":["https://openalex.org/W2018366688","https://openalex.org/W2352178434","https://openalex.org/W2109083503","https://openalex.org/W2351868092","https://openalex.org/W2168755097","https://openalex.org/W1984561329","https://openalex.org/W2047392647","https://openalex.org/W2532935424","https://openalex.org/W2348997984","https://openalex.org/W2387081227"],"abstract_inverted_index":{"The":[0,51,141,171],"Bayesian":[1,20,100],"solution":[2],"is":[3,22,57,78,139,144,165,174,185],"known":[4],"to":[5,67,92,167,178],"be":[6,64,109],"optimal":[7],"for":[8,18,33,81,189],"the":[9,15,19,39,43,54,59,104,129,135,169,182],"symbol-by-symbol":[10],"type":[11],"of":[12,42,46,49,53,61,106,146,149],"equalizer.":[13],"However,":[14],"computational":[16,121,136,183],"complexity":[17,34,137,184],"equalizer":[21,44,143],"usually":[23],"very":[24],"high.":[25],"Signal":[26],"space":[27],"partitioning":[28],"technique":[29],"has":[30],"been":[31],"proposed":[32,172],"reduction.":[35],"It":[36],"was":[37],"shown":[38],"decision":[40],"boundary":[41],"consists":[45],"a":[47,73,89,113,147,155],"set":[48,148],"hyperplanes.":[50],"disadvantage":[52],"existing":[55],"approaches":[56],"that":[58,103],"number":[60,105],"hyperplane":[62],"cannot":[63],"controlled.":[65],"Also,":[66,181],"find":[68],"these":[69],"hyperplanes,":[70],"it":[71],"requires":[72],"state":[74],"searching":[75],"process":[76],"which":[77],"not":[79],"efficient":[80],"time-varying":[82,179],"channels.":[83,180],"In":[84,123],"this":[85,94],"paper,":[86],"we":[87,115,126],"propose":[88,97],"new":[90],"algorithm":[91,173],"remedy":[93],"problem.":[95],"We":[96],"an":[98],"approximate":[99],"criterion":[101],"such":[102],"hyperplanes":[107],"can":[108,116,127],"arbitrarily":[110],"set.":[111],"As":[112],"result,":[114],"trade":[117],"between":[118],"performance":[119,130],"and":[120,154,187],"complexity.":[122],"many":[124],"cases,":[125],"make":[128],"loss":[131],"being":[132],"small":[133],"while":[134],"reduction":[138],"huge.":[140],"resultant":[142],"composed":[145],"parallel":[150],"linear":[151],"discriminant":[152],"functions":[153],"maximum":[156],"operation.":[157],"An":[158],"adaptive":[159],"method":[160],"using":[161],"stochastic":[162],"gradient":[163],"descent":[164],"developed":[166],"identify":[168],"functions.":[170],"then":[175],"inherently":[176],"applicable":[177],"low":[186],"suitable":[188],"realworld":[190],"implementation.":[191]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}