{"id":"https://openalex.org/W2793670130","doi":"https://doi.org/10.1109/globalsip.2017.8308634","title":"Using marginal median and block least mean squares in mobile adaptive networks","display_name":"Using marginal median and block least mean squares in mobile adaptive networks","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2793670130","doi":"https://doi.org/10.1109/globalsip.2017.8308634","mag":"2793670130"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2017.8308634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2017.8308634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","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/A5051404366","display_name":"Fotios Mandanas","orcid":"https://orcid.org/0000-0001-5622-9507"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Fotios Mandanas","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065184406","display_name":"Constantine Kotropoulos","orcid":"https://orcid.org/0000-0001-9939-7930"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Constantine Kotropoulos","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051404366"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.22721654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"5","issue":null,"first_page":"211","last_page":"215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11347","display_name":"Neural Networks Stability and Synchronization","score":0.9937000274658203,"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/T10860","display_name":"Speech and Audio Processing","score":0.9842000007629395,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.646896243095398},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6449838876724243},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5957335233688354},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.47532159090042114},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46773797273635864},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.45041391253471375},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.42316773533821106},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3706706762313843},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35614025592803955},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3168506920337677},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3078380227088928},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.283725768327713}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.646896243095398},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6449838876724243},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5957335233688354},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.47532159090042114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46773797273635864},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.45041391253471375},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.42316773533821106},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3706706762313843},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35614025592803955},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3168506920337677},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3078380227088928},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.283725768327713},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip.2017.8308634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2017.8308634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1564370218","https://openalex.org/W1995375385","https://openalex.org/W1997881026","https://openalex.org/W2012445782","https://openalex.org/W2024307985","https://openalex.org/W2038622372","https://openalex.org/W2042664989","https://openalex.org/W2099175737","https://openalex.org/W2111714602","https://openalex.org/W2117266145","https://openalex.org/W2120286056","https://openalex.org/W2121820607","https://openalex.org/W2127351184","https://openalex.org/W2130359405","https://openalex.org/W2142184324","https://openalex.org/W2154834860","https://openalex.org/W2158491950","https://openalex.org/W2165744313","https://openalex.org/W2295500362","https://openalex.org/W3104550706","https://openalex.org/W4205987271","https://openalex.org/W4238850922"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1977636359","https://openalex.org/W2772305933","https://openalex.org/W2580722822"],"abstract_inverted_index":{"Here,":[0],"we":[1,36],"are":[2],"interested":[3],"in":[4,30,76,109],"the":[5,42,51,54,74,77,81,84,92,103,110,120,127,136,143],"case":[6],"where":[7],"a":[8,27,38,61],"randomly":[9],"chosen":[10],"subset":[11],"of":[12,41,64,71,91,95,106,122],"agents":[13,52,82],"share":[14],"deliberately":[15],"with":[16,22,135],"their":[17,100],"neighbors":[18],"local":[19],"information":[20],"corrupted":[21],"gross":[23],"errors,":[24],"which":[25],"is":[26],"common":[28],"phenomenon":[29],"strategic":[31],"communication.":[32],"Within":[33],"this":[34],"framework,":[35],"propose":[37],"twofold":[39],"extension":[40],"state-of-the-art":[43],"diffusion":[44,131],"adaptation":[45],"techniques":[46],"over":[47],"mobile":[48],"networks.":[49],"First,":[50],"apply":[53],"block":[55],"least":[56],"mean":[57],"squares":[58],"algorithm":[59],"exploiting":[60],"limited":[62],"memory":[63],"prior":[65,69],"regression":[66],"vectors":[67],"and":[68,138],"estimates":[70,98,108],"distance":[72,94],"to":[73],"target":[75],"time":[78],"domain.":[79,112],"Second,":[80],"estimate":[83],"combination":[85],"weights":[86],"based":[87],"on":[88],"negative":[89],"exponentials":[90],"scaled":[93],"intermediate":[96],"location":[97],"within":[99],"neighborhood":[101],"from":[102],"marginal":[104],"median":[105],"these":[107],"spatial":[111],"The":[113],"experimental":[114],"learning":[115],"curves":[116],"demonstrate":[117],"that,":[118],"at":[119],"expense":[121],"some":[123],"additional":[124],"computational":[125],"requirements,":[126],"enhanced":[128],"adapt-then-combine":[129],"(ATC)":[130],"strategy":[132],"can":[133],"cope":[134],"outliers":[137],"yield":[139],"better":[140],"results":[141],"than":[142],"standard":[144],"ATC":[145],"strategy.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}