{"id":"https://openalex.org/W2101437090","doi":"https://doi.org/10.1109/icassp.2005.1416323","title":"Adaptive Complex Wavelet-Based Filtering of EEG for Extraction of Evoked Potential Responses","display_name":"Adaptive Complex Wavelet-Based Filtering of EEG for Extraction of Evoked Potential Responses","publication_year":2006,"publication_date":"2006-10-04","ids":{"openalex":"https://openalex.org/W2101437090","doi":"https://doi.org/10.1109/icassp.2005.1416323","mag":"2101437090"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2005.1416323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1416323","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/A5060440489","display_name":"A. Jacquin","orcid":"https://orcid.org/0000-0003-3182-7329"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Jacquin","raw_affiliation_strings":["Everest Biomedical Instruments"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Everest Biomedical Instruments","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050481327","display_name":"Elvir Causevic","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"E. Causevic","raw_affiliation_strings":["Everest Biomedical Instruments, USA","[Everest Biomedical Instruments, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Everest Biomedical Instruments, USA","institution_ids":[]},{"raw_affiliation_string":"[Everest Biomedical Instruments, USA]","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112721634","display_name":"R. K. Sunil John","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086933","display_name":"NYU Langone Health","ror":"https://ror.org/005dvqh91","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210086933"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. John","raw_affiliation_strings":["NYU Medical Center, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NYU Medical Center, USA","institution_ids":["https://openalex.org/I4210086933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101863660","display_name":"Jelena Kova\u010devi\u0107","orcid":"https://orcid.org/0000-0003-0139-2803"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Kovacevic","raw_affiliation_strings":["Carnegie Mellon University, USA","Carnegie Mellon Univ (USA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon Univ (USA)","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3155,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.61182166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"5","issue":null,"first_page":"393","last_page":"396"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9987999796867371,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9871000051498413,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6522572040557861},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6349729299545288},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.611122727394104},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5842896699905396},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5762045383453369},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.5543936491012573},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5393748879432678},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5100367665290833},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4950973093509674},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.47286057472229004},{"id":"https://openalex.org/keywords/second-generation-wavelet-transform","display_name":"Second-generation wavelet transform","score":0.4464626610279083},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.44563743472099304},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4441242218017578},{"id":"https://openalex.org/keywords/stationary-wavelet-transform","display_name":"Stationary wavelet transform","score":0.4211249351501465},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.3658137321472168},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34560614824295044},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17215877771377563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6522572040557861},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6349729299545288},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.611122727394104},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5842896699905396},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5762045383453369},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.5543936491012573},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5393748879432678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5100367665290833},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4950973093509674},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.47286057472229004},{"id":"https://openalex.org/C111350171","wikidata":"https://www.wikidata.org/wiki/Q7443700","display_name":"Second-generation wavelet transform","level":5,"score":0.4464626610279083},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.44563743472099304},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4441242218017578},{"id":"https://openalex.org/C73339587","wikidata":"https://www.wikidata.org/wiki/Q1375942","display_name":"Stationary wavelet transform","level":5,"score":0.4211249351501465},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.3658137321472168},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34560614824295044},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17215877771377563},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2005.1416323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1416323","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"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.660.1321","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.660.1321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://jelena.ece.cmu.edu/repository/conferences/05_JacquinCJK.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1607525721","https://openalex.org/W1990021147","https://openalex.org/W2003832293","https://openalex.org/W2010441059","https://openalex.org/W2011897157","https://openalex.org/W2049466144","https://openalex.org/W2111252059","https://openalex.org/W2119445186","https://openalex.org/W2128045702","https://openalex.org/W2129276048","https://openalex.org/W2131688689","https://openalex.org/W2146842127","https://openalex.org/W2148080224","https://openalex.org/W2158940042","https://openalex.org/W2170885533","https://openalex.org/W4214806317","https://openalex.org/W4248497145","https://openalex.org/W4249058433"],"related_works":["https://openalex.org/W1506615375","https://openalex.org/W1976022598","https://openalex.org/W2085792030","https://openalex.org/W1588899229","https://openalex.org/W2144408025","https://openalex.org/W2358271565","https://openalex.org/W1986475093","https://openalex.org/W2053682625","https://openalex.org/W68308810","https://openalex.org/W2066485764"],"abstract_inverted_index":{"We":[0,41],"propose":[1],"a":[2,34],"new":[3],"method":[4,66,102],"for":[5,94,109],"the":[6,26,30,56,71,84,100,105],"extraction":[7],"of":[8,23,53,83,88],"auditory":[9],"brainstem":[10],"responses":[11],"(ABRs)":[12],"from":[13],"an":[14,113],"EEG":[15,58,89],"signal.":[16],"It":[17],"is":[18,33],"based":[19,74],"on":[20,75],"adaptive":[21],"filtering":[22,55,69],"signals":[24,111],"in":[25,70],"wavelet":[27,38],"domain,":[28],"where":[29],"transform":[31,39],"used":[32],"nearly":[35],"shift-invariant":[36],"complex":[37],"(CWT).":[40],"compare":[42],"our":[43],"algorithm":[44],"to":[45],"two":[46,107],"existing":[47],"methods.":[48],"The":[49,64],"first":[50],"simply":[51],"consists":[52],"bandpass":[54],"input":[57],"signal":[59],"followed":[60],"by":[61],"linear":[62],"averaging.":[63],"second":[65],"uses":[67],"signal-adaptive":[68],"Fourier":[72],"domain":[73],"phase":[76],"variance":[77],"computed":[78],"at":[79],"each":[80],"spectral":[81],"component":[82],"FFT.":[85],"Realistic":[86],"models":[87],"and":[90],"ABR":[91,110],"are":[92],"generated":[93],"this":[95],"comparison.":[96],"Results":[97],"show":[98],"that":[99],"wavelet-based":[101],"consistently":[103],"outperforms":[104],"other":[106],"methods":[108],"with":[112],"initial":[114],"signal-to-noise":[115],"ratio":[116],"less":[117],"than":[118],"-20":[119],"dB.":[120]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
