{"id":"https://openalex.org/W2891277085","doi":"https://doi.org/10.1109/icassp.2018.8462218","title":"A Tensor Decomposition Technique for Source Localization from Multimodal Data","display_name":"A Tensor Decomposition Technique for Source Localization from Multimodal Data","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2891277085","doi":"https://doi.org/10.1109/icassp.2018.8462218","mag":"2891277085"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8462218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101802022","display_name":"Junting Chen","orcid":"https://orcid.org/0000-0003-3056-9030"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junting Chen","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072739163","display_name":"Urbashi Mitra","orcid":"https://orcid.org/0000-0002-8896-1177"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Urbashi Mitra","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101802022"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.6438,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71193285,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"23","issue":null,"first_page":"4074","last_page":"4078"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.998199999332428,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9947999715805054,"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/tensor","display_name":"Tensor (intrinsic definition)","score":0.7823235392570496},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.6636002063751221},{"id":"https://openalex.org/keywords/tucker-decomposition","display_name":"Tucker decomposition","score":0.6096085906028748},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5641446709632874},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.5641306042671204},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5480738282203674},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5436955094337463},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4982643127441406},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.48312851786613464},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.47084781527519226},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4513886272907257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41789865493774414},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3702331781387329},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.128835529088974},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12346392869949341},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09271088242530823},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08790022134780884},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.07631880044937134}],"concepts":[{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7823235392570496},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.6636002063751221},{"id":"https://openalex.org/C42704193","wikidata":"https://www.wikidata.org/wiki/Q7851097","display_name":"Tucker decomposition","level":4,"score":0.6096085906028748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5641446709632874},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.5641306042671204},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5480738282203674},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5436955094337463},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4982643127441406},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.48312851786613464},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.47084781527519226},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4513886272907257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41789865493774414},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3702331781387329},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.128835529088974},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12346392869949341},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09271088242530823},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08790022134780884},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.07631880044937134},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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.2018.8462218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1606841335","https://openalex.org/W1968154520","https://openalex.org/W1979638981","https://openalex.org/W2015725852","https://openalex.org/W2018282388","https://openalex.org/W2054692776","https://openalex.org/W2079705627","https://openalex.org/W2091407626","https://openalex.org/W2100796177","https://openalex.org/W2102509933","https://openalex.org/W2103542269","https://openalex.org/W2106457743","https://openalex.org/W2107376953","https://openalex.org/W2110407935","https://openalex.org/W2122138733","https://openalex.org/W2122855535","https://openalex.org/W2169967930","https://openalex.org/W2253803609","https://openalex.org/W2404629972","https://openalex.org/W2469230926","https://openalex.org/W2770763863","https://openalex.org/W2798769914","https://openalex.org/W2963956117","https://openalex.org/W6645175440","https://openalex.org/W6678338086","https://openalex.org/W6713343378","https://openalex.org/W6732470269","https://openalex.org/W6746217590","https://openalex.org/W6751091727"],"related_works":["https://openalex.org/W2087995683","https://openalex.org/W2945356277","https://openalex.org/W2901457990","https://openalex.org/W2955092129","https://openalex.org/W2089441007","https://openalex.org/W4283821751","https://openalex.org/W4372260520","https://openalex.org/W3217205658","https://openalex.org/W4312203815","https://openalex.org/W2393920986"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,24,53,57,63,66,74,77,87,94,103,108],"problem":[4],"of":[5,13,23,62,73,114],"localizing":[6],"a":[7,45],"source":[8,88],"based":[9,98],"on":[10,99],"different":[11,17,41,112],"types":[12,113],"signals":[14,25],"measured":[15],"at":[16],"sensing":[18],"locations,":[19],"where":[20,76],"propagation":[21],"models":[22],"are":[26,69,79],"not":[27],"known.":[28],"A":[29],"tensor":[30,64,100],"observation":[31],"model":[32,68],"is":[33,50],"proposed":[34,95],"to":[35,43,86],"arrange":[36],"such":[37],"multimodal":[38],"data":[39,47],"into":[40],"layers":[42],"form":[44],"3D":[46],"array.":[48],"It":[49],"proven":[51],"that":[52,93,105],"vectors":[54,72,78],"extracted":[55],"from":[56,111],"least":[58],"squares":[59],"rank-1":[60],"approximation":[61],"under":[65],"Tucker's":[67],"location":[70],"signature":[71],"source,":[75],"unimodal":[80],"and":[81],"their":[82],"peak":[83],"locations":[84],"correspond":[85],"location.":[89],"Numerical":[90],"experiments":[91],"demonstrate":[92],"localization":[96],"method":[97],"decomposition":[101],"outperforms":[102],"baseline":[104],"heuristically":[106],"averages":[107],"estimates":[109],"individually":[110],"data.":[115]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
