{"id":"https://openalex.org/W1511370431","doi":"https://doi.org/10.1109/ijcnn.2005.1555854","title":"A recurrent RBF network model for nearest neighbor classification","display_name":"A recurrent RBF network model for nearest neighbor classification","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W1511370431","doi":"https://doi.org/10.1109/ijcnn.2005.1555854","mag":"1511370431"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1555854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555854","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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/A5088335258","display_name":"Mehmet K. Muezzinoglu","orcid":null},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M.K. Muezzinoglu","raw_affiliation_strings":["Computational Intelligence Lab., University of Louisville, Louisville, KY, U.S.A","Computational Intelligence Lab., Louisville Univ., KY, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Computational Intelligence Lab., University of Louisville, Louisville, KY, U.S.A","institution_ids":[]},{"raw_affiliation_string":"Computational Intelligence Lab., Louisville Univ., KY, USA#TAB#","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105597450","display_name":"J.M. Zurada","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"J.M. Zurada","raw_affiliation_strings":["Institute of Electrical and Electronics Engineers"],"affiliations":[{"raw_affiliation_string":"Institute of Electrical and Electronics Engineers","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088335258"],"corresponding_institution_ids":["https://openalex.org/I142740786"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.10905923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2","issue":null,"first_page":"343","last_page":"348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9927999973297119,"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/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.7716765403747559},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.6961592435836792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6564509868621826},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.6504579186439514},{"id":"https://openalex.org/keywords/superposition-principle","display_name":"Superposition principle","score":0.609779953956604},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.606175422668457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5618696808815002},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5414716005325317},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5026466846466064},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4823007583618164},{"id":"https://openalex.org/keywords/radial-basis-function-network","display_name":"Radial basis function network","score":0.47161367535591125},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.45562294125556946},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4542428255081177},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4240576922893524},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.42154181003570557},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24632582068443298},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18701666593551636}],"concepts":[{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7716765403747559},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.6961592435836792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6564509868621826},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.6504579186439514},{"id":"https://openalex.org/C27753989","wikidata":"https://www.wikidata.org/wiki/Q284885","display_name":"Superposition principle","level":2,"score":0.609779953956604},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.606175422668457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5618696808815002},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5414716005325317},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5026466846466064},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4823007583618164},{"id":"https://openalex.org/C132917294","wikidata":"https://www.wikidata.org/wiki/Q2679684","display_name":"Radial basis function network","level":4,"score":0.47161367535591125},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.45562294125556946},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4542428255081177},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4240576922893524},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.42154181003570557},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24632582068443298},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18701666593551636},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2005.1555854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555854","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.112.1937","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.1937","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ci.louisville.edu/kerem/evraklar/ijcnn05a.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1531857721","https://openalex.org/W1565956482","https://openalex.org/W1572326640","https://openalex.org/W2061430521","https://openalex.org/W2066815061","https://openalex.org/W2096053111","https://openalex.org/W2113442785","https://openalex.org/W2117453669","https://openalex.org/W2122401586","https://openalex.org/W2128084896","https://openalex.org/W2136827585","https://openalex.org/W2143956139","https://openalex.org/W2150535417","https://openalex.org/W2920943913","https://openalex.org/W4247844322"],"related_works":["https://openalex.org/W4230534566","https://openalex.org/W1992876914","https://openalex.org/W2184586959","https://openalex.org/W2105180757","https://openalex.org/W162769146","https://openalex.org/W2162304341","https://openalex.org/W1567195887","https://openalex.org/W157952102","https://openalex.org/W2471040861","https://openalex.org/W960661091"],"abstract_inverted_index":{"Superposition":[0],"of":[1,12,56,92,101],"radial":[2,45],"basis":[3,46],"functions":[4],"centered":[5],"at":[6],"given":[7],"prototype":[8],"patterns":[9],"constitutes":[10],"one":[11],"the":[13,82,89,93,102],"most":[14],"suitable":[15],"energy":[16,60],"forms":[17],"for":[18],"gradient":[19],"systems":[20],"that":[21,36],"perform":[22],"nearest":[23,67,95],"neighbor":[24,68,96],"classification":[25,78,97],"with":[26],"real-valued":[27],"static":[28],"prototypes.":[29],"It":[30],"is":[31,54,106],"shown":[32],"in":[33],"this":[34],"paper":[35],"a":[37,44,49,73],"continuous-time":[38],"dynamical":[39,77],"neural":[40],"network":[41,83,104],"model,":[42],"employing":[43],"function":[47],"and":[48],"sigmoid":[50],"multilayer":[51],"perceptron":[52],"sub-networks,":[53],"capable":[55],"maximizing":[57],"such":[58],"an":[59],"form":[61],"locally,":[62],"thus":[63],"performing":[64],"almost":[65],"perfectly":[66],"classification,":[69],"when":[70],"initiated":[71],"by":[72,81],"distorted":[74],"pattern.":[75],"The":[76,99],"scheme":[79],"implemented":[80],"eliminates":[84],"all":[85],"comparisons,":[86],"which":[87],"are":[88],"vital":[90],"steps":[91],"conventional":[94],"process.":[98],"performance":[100],"proposed":[103],"model":[105],"demonstrated":[107],"on":[108],"image":[109],"reconstruction":[110],"applications.":[111]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
