{"id":"https://openalex.org/W2787508637","doi":"https://doi.org/10.1109/access.2018.2792329","title":"Where Does Minimum Error Entropy Outperform Minimum Mean Square Error? A New and Closer Look","display_name":"Where Does Minimum Error Entropy Outperform Minimum Mean Square Error? A New and Closer Look","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2787508637","doi":"https://doi.org/10.1109/access.2018.2792329","mag":"2787508637"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2792329","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2792329","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2792329","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060994905","display_name":"Ahmad Reza Heravi","orcid":"https://orcid.org/0000-0002-2481-5867"},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Ahmad Reza Heravi","raw_affiliation_strings":["Electrical Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038472266","display_name":"Ghosheh Abed Hodtani","orcid":"https://orcid.org/0000-0002-4337-1624"},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ghosheh Abed Hodtani","raw_affiliation_strings":["Electrical Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060994905"],"corresponding_institution_ids":["https://openalex.org/I86958956"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.4178,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.65169668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"6","issue":null,"first_page":"5856","last_page":"5864"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9983000159263611,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9980999827384949,"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/mean-squared-error","display_name":"Mean squared error","score":0.6614461541175842},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6310749053955078},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5372481346130371},{"id":"https://openalex.org/keywords/minimum-mean-square-error","display_name":"Minimum mean square error","score":0.5312390327453613},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5253171920776367},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48001235723495483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47932517528533936},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.465268611907959},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4478324055671692},{"id":"https://openalex.org/keywords/mean-square","display_name":"Mean square","score":0.4403775930404663},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4402438700199127},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3953872323036194}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6614461541175842},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6310749053955078},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5372481346130371},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.5312390327453613},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5253171920776367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48001235723495483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47932517528533936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.465268611907959},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4478324055671692},{"id":"https://openalex.org/C2988709989","wikidata":"https://www.wikidata.org/wiki/Q85784623","display_name":"Mean square","level":2,"score":0.4403775930404663},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4402438700199127},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3953872323036194},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2792329","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2792329","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ff2df474e3d641948e643bac8a543876","is_oa":true,"landing_page_url":"https://doaj.org/article/ff2df474e3d641948e643bac8a543876","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 5856-5864 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2792329","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2792329","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321722","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W206162032","https://openalex.org/W1069729739","https://openalex.org/W1624804034","https://openalex.org/W1804536132","https://openalex.org/W1886566350","https://openalex.org/W1966468545","https://openalex.org/W1978003802","https://openalex.org/W1980907873","https://openalex.org/W1984664396","https://openalex.org/W2003906560","https://openalex.org/W2010824005","https://openalex.org/W2011292340","https://openalex.org/W2019034316","https://openalex.org/W2026581470","https://openalex.org/W2030930526","https://openalex.org/W2044351729","https://openalex.org/W2068785790","https://openalex.org/W2097521973","https://openalex.org/W2104433269","https://openalex.org/W2105295604","https://openalex.org/W2113713615","https://openalex.org/W2116801843","https://openalex.org/W2118020555","https://openalex.org/W2132811361","https://openalex.org/W2135160607","https://openalex.org/W2136409657","https://openalex.org/W2139272549","https://openalex.org/W2141767566","https://openalex.org/W2148665023","https://openalex.org/W2165898564","https://openalex.org/W2256521743","https://openalex.org/W2291607627","https://openalex.org/W2316011343","https://openalex.org/W2316437979","https://openalex.org/W2395240779","https://openalex.org/W2432461368","https://openalex.org/W2591573516","https://openalex.org/W2606822099","https://openalex.org/W2698658463","https://openalex.org/W4230367971","https://openalex.org/W4285719527","https://openalex.org/W6677267524","https://openalex.org/W6682142706","https://openalex.org/W6781870204"],"related_works":["https://openalex.org/W2075897667","https://openalex.org/W2907746047","https://openalex.org/W3125536267","https://openalex.org/W2073909383","https://openalex.org/W2274645452","https://openalex.org/W2949310342","https://openalex.org/W2166435121","https://openalex.org/W1612475656","https://openalex.org/W242755951","https://openalex.org/W2738279990"],"abstract_inverted_index":{"The":[0,59],"past":[1],"decade":[2],"has":[3],"seen":[4,28],"a":[5,97,114],"rapid":[6],"application":[7],"of":[8,61,70,75,120],"information":[9,45],"theoretic":[10,46,110],"learning":[11,20],"(ITL)":[12],"criteria":[13,47],"in":[14,23,88],"robust":[15],"signal":[16],"processing":[17],"and":[18,104],"machine":[19],"problems.":[21],"Generally,":[22],"ITL's":[24],"literature,":[25],"it":[26],"is":[27,64],"that,":[29],"under":[30,92],"non-Gaussian":[31,43,90],"assumptions,":[32],"especially":[33],"when":[34],"the":[35,89,109,118],"data":[36],"are":[37],"corrupted":[38],"by":[39],"heavy-tailed":[40],"or":[41],"multi-modal":[42],"distributions,":[44],"[such":[48],"as":[49],"minimum":[50,76],"error":[51],"entropy":[52],"(MEE)]":[53],"outperform":[54],"second":[55],"order":[56],"statistical":[57],"ones.":[58],"objective":[60],"this":[62,67,101],"research":[63],"to":[65],"investigate":[66],"better":[68,115],"performance":[69],"MEE":[71,121],"criterion":[72],"against":[73],"that":[74],"mean":[77],"square":[78],"error.":[79],"Having":[80],"found":[81],"similar":[82],"results":[83],"for":[84,117],"MEEand":[85],"MSE-based":[86],"methods,":[87],"environment":[91],"particular":[93],"conditions,":[94],"we":[95,112],"need":[96],"precise":[98],"demarcation":[99],"between":[100],"occasional":[102,105],"similarity":[103],"outperformance.":[106],"Based":[107],"on":[108],"findings,":[111],"reveal":[113],"touchstone":[116],"outperformance":[119],"versus":[122],"MSE.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}