{"id":"https://openalex.org/W2590565095","doi":"https://doi.org/10.1109/icci-cc.2016.7862094","title":"Hebbian learning and the LMS algorithm","display_name":"Hebbian learning and the LMS algorithm","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2590565095","doi":"https://doi.org/10.1109/icci-cc.2016.7862094","mag":"2590565095"},"language":"en","primary_location":{"id":"doi:10.1109/icci-cc.2016.7862094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","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/A5044542575","display_name":"Bernard Widrow","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]},{"id":"https://openalex.org/I1324840837","display_name":"Hewlett-Packard (United States)","ror":"https://ror.org/059rn9488","country_code":"US","type":"company","lineage":["https://openalex.org/I1324840837"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bernard Widrow","raw_affiliation_strings":["Dept. of Packard Electrical Engineering, Stanford University, Stanford, CA"],"affiliations":[{"raw_affiliation_string":"Dept. of Packard Electrical Engineering, Stanford University, Stanford, CA","institution_ids":["https://openalex.org/I1324840837","https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5044542575"],"corresponding_institution_ids":["https://openalex.org/I1324840837","https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":2.9993,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.93174686,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.6241999864578247,"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":0.6241999864578247,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hebbian-theory","display_name":"Hebbian theory","score":0.9053691625595093},{"id":"https://openalex.org/keywords/leabra","display_name":"Leabra","score":0.8590123653411865},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.8506104946136475},{"id":"https://openalex.org/keywords/competitive-learning","display_name":"Competitive learning","score":0.8398009538650513},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7285846471786499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.621333122253418},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5500206351280212},{"id":"https://openalex.org/keywords/wake-sleep-algorithm","display_name":"Wake-sleep algorithm","score":0.5096192359924316},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4517081677913666},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4441828429698944},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4356839060783386},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36125892400741577},{"id":"https://openalex.org/keywords/generalization-error","display_name":"Generalization error","score":0.07323074340820312}],"concepts":[{"id":"https://openalex.org/C111437709","wikidata":"https://www.wikidata.org/wiki/Q1277874","display_name":"Hebbian theory","level":3,"score":0.9053691625595093},{"id":"https://openalex.org/C97108695","wikidata":"https://www.wikidata.org/wiki/Q6508265","display_name":"Leabra","level":5,"score":0.8590123653411865},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.8506104946136475},{"id":"https://openalex.org/C120822770","wikidata":"https://www.wikidata.org/wiki/Q5156355","display_name":"Competitive learning","level":3,"score":0.8398009538650513},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7285846471786499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.621333122253418},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5500206351280212},{"id":"https://openalex.org/C17061570","wikidata":"https://www.wikidata.org/wiki/Q7960888","display_name":"Wake-sleep algorithm","level":4,"score":0.5096192359924316},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4517081677913666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4441828429698944},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4356839060783386},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36125892400741577},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.07323074340820312}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icci-cc.2016.7862094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2590565095","https://openalex.org/W4387853727","https://openalex.org/W1950019275","https://openalex.org/W2896927215","https://openalex.org/W2899454144","https://openalex.org/W3180828476","https://openalex.org/W1483579134","https://openalex.org/W2160735767","https://openalex.org/W1773430112","https://openalex.org/W2070263870"],"abstract_inverted_index":{"Summary":[0],"form":[1,42],"only":[2],"given.":[3],"Hebbian":[4,32,55],"learning":[5,30,33,37,51,65,76,87,95],"is":[6,24,34,38],"one":[7],"of":[8,12,20,43],"the":[9,25,58,101,109],"fundamental":[10,82],"premises":[11],"neuroscience.":[13],"The":[14,94],"LMS":[15,36,44],"(least":[16],"mean":[17],"square)":[18],"algorithm":[19,66,96],"Widrow":[21],"and":[22,52,72,103],"Hoff":[23],"world's":[26],"most":[27],"widely":[28],"used":[29],"algorithm.":[31,111],"unsupervised.":[35],"supervised.":[39],"However,":[40],"a":[41,62],"can":[45],"be":[46,108],"constructed":[47],"to":[48,53],"perform":[49],"unsupervised":[50,64],"implement":[54],"learning.":[56],"Combining":[57],"two":[59],"paradigms":[60],"creates":[61],"new":[63],"that":[67],"has":[68],"practical":[69],"engineering":[70],"applications":[71],"provides":[73],"insight":[74],"into":[75],"in":[77,90],"living":[78,91],"neural":[79,92],"networks.":[80],"A":[81],"question":[83],"is,":[84],"how":[85],"does":[86],"take":[88],"place":[89],"networks?":[93],"practiced":[97],"by":[98],"nature":[99],"at":[100],"neuron":[102],"synapse":[104],"level":[105],"may":[106],"well":[107],"Hebbian-LMS":[110]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}