{"id":"https://openalex.org/W2003121793","doi":"https://doi.org/10.1109/icdsp.2013.6622759","title":"Robust multi-dimensional model order estimation in the presence of brief sensor failures","display_name":"Robust multi-dimensional model order estimation in the presence of brief sensor failures","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2003121793","doi":"https://doi.org/10.1109/icdsp.2013.6622759","mag":"2003121793"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2013.6622759","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2013.6622759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 18th International Conference on Digital Signal Processing (DSP)","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":null,"display_name":"Yao Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Yao Cheng","raw_affiliation_strings":["Communications Research Laboratory, Ilmenau University of Technology, Ilmenau, Germany","[Commun. Res. Lab., Ilmenau Univ. of Technol., Ilmenau, Germany]"],"affiliations":[{"raw_affiliation_string":"Communications Research Laboratory, Ilmenau University of Technology, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]},{"raw_affiliation_string":"[Commun. Res. Lab., Ilmenau Univ. of Technol., Ilmenau, Germany]","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004533757","display_name":"Martin Haardt","orcid":"https://orcid.org/0000-0001-7810-975X"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Haardt","raw_affiliation_strings":["Communications Research Laboratory, Ilmenau University of Technology, Ilmenau, Germany","[Commun. Res. Lab., Ilmenau Univ. of Technol., Ilmenau, Germany]"],"affiliations":[{"raw_affiliation_string":"Communications Research Laboratory, Ilmenau University of Technology, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]},{"raw_affiliation_string":"[Commun. Res. Lab., Ilmenau Univ. of Technol., Ilmenau, Germany]","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I119449181"],"apc_list":null,"apc_paid":null,"fwci":0.9646,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74169742,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"56","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9976999759674072,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9976999759674072,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9957000017166138,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/akaike-information-criterion","display_name":"Akaike information criterion","score":0.9096479415893555},{"id":"https://openalex.org/keywords/minimum-description-length","display_name":"Minimum description length","score":0.777588963508606},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7245479822158813},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6361478567123413},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.6153275966644287},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5978424549102783},{"id":"https://openalex.org/keywords/bayesian-information-criterion","display_name":"Bayesian information criterion","score":0.5206824541091919},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5147164463996887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5114108920097351},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5097097754478455},{"id":"https://openalex.org/keywords/robust-statistics","display_name":"Robust statistics","score":0.4830389618873596},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48129239678382874},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4307989776134491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.300739586353302},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15126174688339233}],"concepts":[{"id":"https://openalex.org/C126674687","wikidata":"https://www.wikidata.org/wiki/Q1662573","display_name":"Akaike information criterion","level":2,"score":0.9096479415893555},{"id":"https://openalex.org/C87465248","wikidata":"https://www.wikidata.org/wiki/Q1417790","display_name":"Minimum description length","level":2,"score":0.777588963508606},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7245479822158813},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6361478567123413},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.6153275966644287},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5978424549102783},{"id":"https://openalex.org/C168136583","wikidata":"https://www.wikidata.org/wiki/Q1988242","display_name":"Bayesian information criterion","level":2,"score":0.5206824541091919},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5147164463996887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5114108920097351},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5097097754478455},{"id":"https://openalex.org/C67226441","wikidata":"https://www.wikidata.org/wiki/Q1665389","display_name":"Robust statistics","level":3,"score":0.4830389618873596},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48129239678382874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4307989776134491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.300739586353302},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15126174688339233},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdsp.2013.6622759","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2013.6622759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 18th International Conference on Digital Signal Processing (DSP)","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":14,"referenced_works":["https://openalex.org/W4242002","https://openalex.org/W1563108151","https://openalex.org/W1982733046","https://openalex.org/W1999177119","https://openalex.org/W2034248602","https://openalex.org/W2096710051","https://openalex.org/W2096783889","https://openalex.org/W2136210023","https://openalex.org/W2147863695","https://openalex.org/W2160664759","https://openalex.org/W2537590324","https://openalex.org/W2545903769","https://openalex.org/W2977886060","https://openalex.org/W3197189799"],"related_works":["https://openalex.org/W3122388856","https://openalex.org/W2423290227","https://openalex.org/W2114625140","https://openalex.org/W2509820422","https://openalex.org/W2783425804","https://openalex.org/W2963415778","https://openalex.org/W2544537192","https://openalex.org/W2148249824","https://openalex.org/W2033907215","https://openalex.org/W3202195698"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"a":[3,57,120],"robust":[4,40,47,81,105,108,112,137],"version":[5],"of":[6,30,36,69,79,85,92,95,104,133,145],"the":[7,23,28,37,67,70,77,80,87,93,96,130,134,143],"tensor-based":[8,136],"model":[9,24,138],"order":[10,25,139],"selection":[11,140],"technique":[12],"R-D":[13,41,48,106,109,113],"Exponential":[14],"Fitting":[15],"Test":[16],"(EFT)":[17],"is":[18,64],"developed":[19],"to":[20,128],"deal":[21],"with":[22],"estimation":[26],"in":[27,142],"presence":[29,144],"brief":[31,146],"sensor":[32,147],"failures.":[33,148],"Moreover,":[34],"extensions":[35],"previously":[38],"proposed":[39,54,135],"Akaike's":[42],"Information":[43],"Criterion":[44],"(AIC)":[45],"and":[46,89,111,119],"Minimum":[49],"Description":[50],"Length":[51],"(MDL)":[52],"are":[53,74,126],"by":[55],"constructing":[56],"real-valued":[58,71],"measurement":[59,99],"tensor":[60,73],"where":[61],"forward-backward":[62],"averaging":[63],"incorporated.":[65],"Then":[66],"unfoldings":[68,94],"data":[72],"used":[75],"as":[76],"input":[78],"covariance":[82],"estimator":[83],"instead":[84],"stacking":[86],"real":[88],"imaginary":[90],"parts":[91],"original":[97],"complex-valued":[98],"tensor.":[100],"Such":[101],"enhanced":[102],"versions":[103],"AIC,":[107],"MDL,":[110],"EFT":[114],"experience":[115],"an":[116],"improved":[117],"performance":[118],"reduced":[121],"computational":[122],"complexity.":[123],"Numerical":[124],"simulations":[125],"performed":[127],"demonstrate":[129],"promising":[131],"performances":[132],"techniques":[141]},"counts_by_year":[{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}