{"id":"https://openalex.org/W2112662673","doi":"https://doi.org/10.1109/icnc.2011.6022046","title":"Optimal fuzzy competitive learning self-organizing feature map","display_name":"Optimal fuzzy competitive learning self-organizing feature map","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2112662673","doi":"https://doi.org/10.1109/icnc.2011.6022046","mag":"2112662673"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2011.6022046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2011.6022046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 Seventh International Conference on Natural Computation","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/A5100450760","display_name":"Ling Zhang","orcid":"https://orcid.org/0000-0003-1124-3545"},"institutions":[{"id":"https://openalex.org/I105991555","display_name":"Jingdezhen Ceramic Institute","ror":"https://ror.org/01d0jcz74","country_code":"CN","type":"education","lineage":["https://openalex.org/I105991555"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ling Zhang","raw_affiliation_strings":["Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, Jingdezhen, China","Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, China"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, Jingdezhen, China","institution_ids":["https://openalex.org/I105991555"]},{"raw_affiliation_string":"Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, China","institution_ids":["https://openalex.org/I105991555"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058858060","display_name":"Hao Feng","orcid":"https://orcid.org/0009-0002-1478-2747"},"institutions":[{"id":"https://openalex.org/I105991555","display_name":"Jingdezhen Ceramic Institute","ror":"https://ror.org/01d0jcz74","country_code":"CN","type":"education","lineage":["https://openalex.org/I105991555"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Feng","raw_affiliation_strings":["Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, Jingdezhen, China","Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, China"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, Jingdezhen, China","institution_ids":["https://openalex.org/I105991555"]},{"raw_affiliation_string":"Department of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, China","institution_ids":["https://openalex.org/I105991555"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044019139","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0002-2189-7801"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["New Providence, NJ, Lucent Technologies, Inc., U.S.A","Lucent Technologies, Inc., New Providence, NJ, U.S.A"],"affiliations":[{"raw_affiliation_string":"New Providence, NJ, Lucent Technologies, Inc., U.S.A","institution_ids":[]},{"raw_affiliation_string":"Lucent Technologies, Inc., New Providence, NJ, U.S.A","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100450760"],"corresponding_institution_ids":["https://openalex.org/I105991555"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12187706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"145","issue":null,"first_page":"436","last_page":"439"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9973999857902527,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9973999857902527,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9846000075340271,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9652000069618225,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.5967661738395691},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5800196528434753},{"id":"https://openalex.org/keywords/competitive-learning","display_name":"Competitive learning","score":0.5710848569869995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.540115475654602},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5180283188819885},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.4823440909385681},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47088393568992615},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4261088967323303},{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.4230259656906128},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4217148423194885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38599830865859985},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3542637825012207},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2823724150657654},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2701561450958252}],"concepts":[{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.5967661738395691},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5800196528434753},{"id":"https://openalex.org/C120822770","wikidata":"https://www.wikidata.org/wiki/Q5156355","display_name":"Competitive learning","level":3,"score":0.5710848569869995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.540115475654602},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5180283188819885},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.4823440909385681},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47088393568992615},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4261088967323303},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.4230259656906128},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4217148423194885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38599830865859985},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3542637825012207},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2823724150657654},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2701561450958252},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2011.6022046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2011.6022046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 Seventh International Conference on Natural Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8299999833106995,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1608472120","https://openalex.org/W1634005169","https://openalex.org/W1990992471","https://openalex.org/W1991848143","https://openalex.org/W2113076747","https://openalex.org/W2134383396","https://openalex.org/W2136276313"],"related_works":["https://openalex.org/W2148772884","https://openalex.org/W2352648934","https://openalex.org/W2170599662","https://openalex.org/W2145213141","https://openalex.org/W2071781501","https://openalex.org/W3148658660","https://openalex.org/W4243803532","https://openalex.org/W2389977222","https://openalex.org/W2100492357","https://openalex.org/W1990646304"],"abstract_inverted_index":{"In":[0],"this":[1,58,101,118],"paper,":[2,59],"we":[3],"introduce":[4],"a":[5,124],"novel":[6,49],"optimal":[7,50,82,102,111,119],"fuzzy":[8,33,63],"competitive":[9,34],"learning":[10],"self-organizing":[11],"feature":[12],"map":[13],"(FCL-SOFM.).":[14],"Different":[15],"from":[16],"traditional":[17],"SOFM,":[18],"the":[19,26,32,62,70,89],"neurons":[20],"in":[21,25,46,57,60,77,106],"FCL-SOFM":[22,83,103],"are":[23],"updated":[24],"whole":[27],"neuron":[28],"lattice":[29],"based":[30,68],"on":[31],"membership":[35,41,51],"function.":[36],"So,":[37],"how":[38],"to":[39,88,109],"choose":[40],"function":[42,52],"is":[43,55,66],"very":[44],"important":[45],"FCL-SOFM.":[47],"A":[48],"selection":[53],"scheme":[54],"proposed":[56],"which":[61],"exponential":[64],"factor":[65],"chosen":[67],"upon":[69],"normalized":[71],"Gibbs":[72],"distribution":[73],"of":[74,92],"network":[75,84,105],"energy":[76],"each":[78],"iterative":[79],"stage.":[80],"This":[81],"can":[85],"finally":[86],"converge":[87],"base":[90],"state":[91],"system":[93],"energy,":[94],"and":[95],"achieve":[96],"global":[97],"minimum.":[98],"We":[99],"apply":[100],"neural":[104],"Vector":[107,121],"Quantization":[108,122],"construct":[110],"codebook.":[112],"The":[113],"experimental":[114],"result":[115],"shows":[116],"that":[117],"FCL_SOFM":[120],"has":[123],"better":[125],"compressing":[126],"performance":[127],"than":[128],"JPEG.":[129]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}