{"id":"https://openalex.org/W1920841386","doi":"https://doi.org/10.1109/tsp.2014.2323021","title":"Distributed State Estimation With Dimension Reduction Preprocessing","display_name":"Distributed State Estimation With Dimension Reduction Preprocessing","publication_year":2014,"publication_date":"2014-05-09","ids":{"openalex":"https://openalex.org/W1920841386","doi":"https://doi.org/10.1109/tsp.2014.2323021","mag":"1920841386"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2014.2323021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2014.2323021","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-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/A5102858914","display_name":"Hang Ma","orcid":"https://orcid.org/0000-0003-3397-5245"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hang Ma","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076187162","display_name":"Yuhan Yang","orcid":"https://orcid.org/0000-0001-7314-5161"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu-Han Yang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100530319","display_name":"Yan Chen","orcid":"https://orcid.org/0009-0009-9778-043X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032395820","display_name":"K. J. Ray Liu","orcid":"https://orcid.org/0000-0001-5469-5811"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. J. Ray Liu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341290","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0002-3520-6450"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Electrical & Comput. Eng., Univ. of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8791,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.91167101,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"62","issue":"12","first_page":"3098","last_page":"3110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9995999932289124,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/estimator","display_name":"Estimator","score":0.6873912811279297},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.619575560092926},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.6122143268585205},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5944528579711914},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5457261800765991},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4647108316421509},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4632837176322937},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4469074606895447},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4431624114513397},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4409499764442444},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4295438826084137},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3629359304904938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11989825963973999},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09084045886993408}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6873912811279297},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.619575560092926},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.6122143268585205},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5944528579711914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5457261800765991},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4647108316421509},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4632837176322937},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4469074606895447},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4431624114513397},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4409499764442444},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4295438826084137},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3629359304904938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11989825963973999},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09084045886993408},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2014.2323021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2014.2323021","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.465.6808","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.465.6808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://sig.umd.edu/publications/Ma_TSP_201406.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1573301526","https://openalex.org/W1650518998","https://openalex.org/W1972642170","https://openalex.org/W1974963694","https://openalex.org/W1980550829","https://openalex.org/W1986092017","https://openalex.org/W2000043590","https://openalex.org/W2004026774","https://openalex.org/W2007239301","https://openalex.org/W2020587804","https://openalex.org/W2030949386","https://openalex.org/W2043791244","https://openalex.org/W2067982037","https://openalex.org/W2085352907","https://openalex.org/W2085837659","https://openalex.org/W2089105767","https://openalex.org/W2101847234","https://openalex.org/W2102300181","https://openalex.org/W2106424475","https://openalex.org/W2116052628","https://openalex.org/W2117561657","https://openalex.org/W2118550318","https://openalex.org/W2119193463","https://openalex.org/W2121305759","https://openalex.org/W2150674381","https://openalex.org/W2154828437","https://openalex.org/W2154961923","https://openalex.org/W2162849585","https://openalex.org/W2165489013","https://openalex.org/W2168161970","https://openalex.org/W2170239483","https://openalex.org/W2171206152","https://openalex.org/W2279187459","https://openalex.org/W2495701169","https://openalex.org/W2532668254","https://openalex.org/W2610857016","https://openalex.org/W4229706427","https://openalex.org/W6636846757"],"related_works":["https://openalex.org/W2357461155","https://openalex.org/W2384129116","https://openalex.org/W2354251581","https://openalex.org/W1607154928","https://openalex.org/W2766721049","https://openalex.org/W3145924829","https://openalex.org/W2353647904","https://openalex.org/W3152267458","https://openalex.org/W2087937280","https://openalex.org/W2767307537"],"abstract_inverted_index":{"System":[0],"state":[1],"estimation":[2,107,149],"relies":[3],"heavily":[4],"on":[5,33,58,122],"the":[6,9,14,34,53,63,69,74,83,86,94,123,126,132,136,145,172,175,183,192,211,214],"measurements.":[7],"With":[8],"advance":[10],"of":[11,55,85,125,213],"sensing":[12],"technology,":[13],"ability":[15],"to":[16,51,81,100,161,163,167,209],"measure":[17],"is":[18,108,114,118,134,159],"no":[19],"longer":[20],"a":[21,119,140,164],"bottleneck":[22],"in":[23,110,171,203],"many":[24],"systems,":[25,68],"and":[26,28,76,103],"more":[27,29],"researchers":[30],"now":[31],"focus":[32],"rich-information":[35],"setting,":[36],"i.e.,":[37],"big":[38],"data.":[39],"However,":[40],"although":[41],"information":[42],"never":[43],"hurts,":[44],"it":[45,56,79],"does":[46],"not":[47],"help":[48],"unconditionally.":[49],"How":[50],"make":[52],"most":[54],"depends":[57],"whether":[59],"we":[60,154],"can":[61,150],"process":[62],"data":[64,128],"efficiently.":[65],"In":[66],"some":[67,197],"inherent":[70],"constraint":[71],"such":[72,129],"as":[73],"bandwidth":[75],"cost":[77],"makes":[78],"necessary":[80],"reduce":[82,101],"dimension":[84],"measurement":[87],"before":[88],"further":[89],"processing.":[90],"The":[91],"problem":[92],"that":[93,116,130,144,158,174],"raw":[95],"measurements":[96],"are":[97,207],"first":[98],"preprocessed":[99,127],"size":[102,124,133],"then":[104],"used":[105],"for":[106],"addressed":[109],"this":[111],"paper.":[112],"It":[113],"shown":[115,208],"there":[117,138],"lower":[120,176],"bound":[121,177],"if":[131],"beyond":[135],"bound,":[137],"exists":[139],"closed-form":[141],"estimator":[142,170],"design":[143,168],"linear":[146],"minimum":[147],"mean-square":[148],"be":[151,179],"obtained.":[152],"Moreover,":[153],"propose":[155],"an":[156,169],"algorithm":[157,185],"guaranteed":[160],"converge":[162],"stationary":[165],"point":[166],"conditions":[173],"cannot":[178],"reached.":[180],"Besides":[181],"convergence,":[182],"proposed":[184,215],"guarantees":[186],"bounded":[187],"performance":[188],"loss":[189],"compared":[190],"with":[191],"global":[193],"optimal":[194],"solution":[195],"under":[196],"additional":[198],"conditions.":[199],"Finally,":[200],"simulation":[201],"results":[202],"three":[204],"different":[205],"applications":[206],"demonstrate":[210],"effectiveness":[212],"algorithm.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}