{"id":"https://openalex.org/W2159670994","doi":"https://doi.org/10.1109/icassp.2005.1416048","title":"EM-driven Stereo-like Gaussian Chirplet Mixture Estimation","display_name":"EM-driven Stereo-like Gaussian Chirplet Mixture Estimation","publication_year":2006,"publication_date":"2006-10-11","ids":{"openalex":"https://openalex.org/W2159670994","doi":"https://doi.org/10.1109/icassp.2005.1416048","mag":"2159670994"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2005.1416048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1416048","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":"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/A5039134673","display_name":"Luis Weruaga","orcid":null},"institutions":[{"id":"https://openalex.org/I138211613","display_name":"Austrian Academy of Sciences","ror":"https://ror.org/03anc3s24","country_code":"AT","type":"government","lineage":["https://openalex.org/I138211613"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Luis Weruaga","raw_affiliation_strings":["Commission for Scientific Visualization, Austrian Academy of Sciences, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Commission for Scientific Visualization, Austrian Academy of Sciences, Vienna, Austria","institution_ids":["https://openalex.org/I138211613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110015167","display_name":"Mariacn Kepesi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122474","display_name":"Forschungszentrum Telekommunikation Wien","ror":"https://ror.org/026nftk33","country_code":"AT","type":"facility","lineage":["https://openalex.org/I4210122474"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"M. Kepesi","raw_affiliation_strings":["Telecommunications Research Center, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Telecommunications Research Center, Vienna, Austria","institution_ids":["https://openalex.org/I4210122474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.8087,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.9517491,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"4","issue":null,"first_page":"473","last_page":"476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9811000227928162,"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"}},"topics":[{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9811000227928162,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.975600004196167,"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/T11665","display_name":"Animal Vocal Communication and Behavior","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/1309","display_name":"Developmental Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/chirp","display_name":"Chirp","score":0.881024956703186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6836128234863281},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5696820020675659},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.552187442779541},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5303982496261597},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.5301096439361572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5295646786689758},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5216286778450012},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.50909823179245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5005269050598145},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.48242005705833435},{"id":"https://openalex.org/keywords/human-echolocation","display_name":"Human echolocation","score":0.4784258008003235},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.44172239303588867},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43182119727134705},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.4275393486022949},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.42697012424468994},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38647714257240295},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.21257135272026062},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20742332935333252},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.1998918354511261},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.11500081419944763},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09053614735603333},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.07185816764831543},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06760898232460022}],"concepts":[{"id":"https://openalex.org/C132794960","wikidata":"https://www.wikidata.org/wiki/Q27304","display_name":"Chirp","level":3,"score":0.881024956703186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6836128234863281},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5696820020675659},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.552187442779541},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5303982496261597},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.5301096439361572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5295646786689758},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5216286778450012},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.50909823179245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5005269050598145},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.48242005705833435},{"id":"https://openalex.org/C167954536","wikidata":"https://www.wikidata.org/wiki/Q1920844","display_name":"Human echolocation","level":2,"score":0.4784258008003235},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.44172239303588867},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43182119727134705},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.4275393486022949},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.42697012424468994},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38647714257240295},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.21257135272026062},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20742332935333252},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.1998918354511261},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.11500081419944763},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09053614735603333},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.07185816764831543},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06760898232460022},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2005.1416048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1416048","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332222","display_name":"University of Illinois at Urbana-Champaign","ror":"https://ror.org/047426m28"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W151159629","https://openalex.org/W2008169417","https://openalex.org/W2078938486","https://openalex.org/W2105216472","https://openalex.org/W2117761544","https://openalex.org/W2134283197","https://openalex.org/W2151693816","https://openalex.org/W2158706760","https://openalex.org/W2159981869","https://openalex.org/W2293669764","https://openalex.org/W6683157835"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W84255947","https://openalex.org/W2141591718","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2061347451"],"abstract_inverted_index":{"This":[0,71],"paper":[1],"proposes":[2],"a":[3,12,17,28,45,75,90,105],"novel":[4],"technique":[5,20,72,96],"for":[6,101,109],"the":[7,23,34,51,86,98,102],"time-frequency":[8],"(TF)":[9],"estimation":[10,53],"of":[11,25,30,33,89,104],"Gaussian":[13],"chirplet":[14,52],"mixture":[15],"in":[16,43],"signal.":[18],"The":[19,55,94],"relies":[21],"on":[22,74],"combination":[24],"one":[26],"and":[27,36],"half-worth":[29],"chirp":[31],"transform":[32],"signal":[35],"an":[37,62],"expectation":[38],"maximization-driven":[39],"blind":[40],"identification":[41],"algorithm,":[42],"such":[44],"way":[46],"that":[47],"it":[48],"carries":[49],"out":[50],"in-segment.":[54],"mechanism":[56],"resembles":[57],"stereo":[58],"processing":[59,77,108],"while":[60],"keeping":[61],"interesting":[63],"biological":[64],"parallel":[65,106],"with":[66],"auditory":[67],"cortex":[68],"artificial":[69],"models.":[70],"applied":[73],"short-time":[76],"basis":[78,100],"is":[79],"shown":[80],"to":[81],"be":[82],"accurate":[83],"at":[84],"identifying":[85],"TF":[87],"composition":[88],"bat":[91],"echolocation":[92],"chirp.":[93],"proposed":[95],"represents":[97],"initial":[99],"development":[103],"hierarchic":[107],"more":[110],"ambitious":[111],"objectives.":[112]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}