{"id":"https://openalex.org/W2113743072","doi":"https://doi.org/10.1109/fuzzy.2005.1452416","title":"A Switched-Resistor Approach to Hardware Implementation of Neural Networks","display_name":"A Switched-Resistor Approach to Hardware Implementation of Neural Networks","publication_year":2005,"publication_date":"2005-07-28","ids":{"openalex":"https://openalex.org/W2113743072","doi":"https://doi.org/10.1109/fuzzy.2005.1452416","mag":"2113743072"},"language":"en","primary_location":{"id":"doi:10.1109/fuzzy.2005.1452416","is_oa":false,"landing_page_url":"http://doi.org/10.1109/fuzzy.2005.1452416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05.","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/A5026794628","display_name":"Nian Zhang","orcid":"https://orcid.org/0000-0003-1916-7719"},"institutions":[{"id":"https://openalex.org/I184647316","display_name":"South Dakota School of Mines and Technology","ror":"https://ror.org/00ch7yk27","country_code":"US","type":"education","lineage":["https://openalex.org/I184647316"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nian Zhang","raw_affiliation_strings":["Dept. of Electr. & Comput. Eng., South Dakota Sch. of Mines & Technol., Rapid City, SD"],"affiliations":[{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., South Dakota Sch. of Mines & Technol., Rapid City, SD","institution_ids":["https://openalex.org/I184647316"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038037619","display_name":"Donald C. Wunsch","orcid":"https://orcid.org/0000-0002-9726-9051"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D.C. Wunsch","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026794628"],"corresponding_institution_ids":["https://openalex.org/I184647316"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.13396152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"336","last_page":"340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9993000030517578,"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":0.9993000030517578,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/resistor","display_name":"Resistor","score":0.766146183013916},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7284687757492065},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6633327007293701},{"id":"https://openalex.org/keywords/modularity","display_name":"Modularity (biology)","score":0.6562861800193787},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.5614134669303894},{"id":"https://openalex.org/keywords/physical-neural-network","display_name":"Physical neural network","score":0.46969082951545715},{"id":"https://openalex.org/keywords/analogue-electronics","display_name":"Analogue electronics","score":0.45876070857048035},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.4409748911857605},{"id":"https://openalex.org/keywords/synapse","display_name":"Synapse","score":0.43904542922973633},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.41928496956825256},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.40477555990219116},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.31184977293014526},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.24043864011764526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21589884161949158},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1708831787109375},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15385505557060242},{"id":"https://openalex.org/keywords/types-of-artificial-neural-networks","display_name":"Types of artificial neural networks","score":0.09746173024177551},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.07485213875770569}],"concepts":[{"id":"https://openalex.org/C137488568","wikidata":"https://www.wikidata.org/wiki/Q5321","display_name":"Resistor","level":3,"score":0.766146183013916},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7284687757492065},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6633327007293701},{"id":"https://openalex.org/C2779478453","wikidata":"https://www.wikidata.org/wiki/Q6889748","display_name":"Modularity (biology)","level":2,"score":0.6562861800193787},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.5614134669303894},{"id":"https://openalex.org/C33766855","wikidata":"https://www.wikidata.org/wiki/Q7189618","display_name":"Physical neural network","level":5,"score":0.46969082951545715},{"id":"https://openalex.org/C29074008","wikidata":"https://www.wikidata.org/wiki/Q174925","display_name":"Analogue electronics","level":3,"score":0.45876070857048035},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.4409748911857605},{"id":"https://openalex.org/C127445978","wikidata":"https://www.wikidata.org/wiki/Q187181","display_name":"Synapse","level":2,"score":0.43904542922973633},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.41928496956825256},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.40477555990219116},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.31184977293014526},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.24043864011764526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21589884161949158},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1708831787109375},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15385505557060242},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.09746173024177551},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.07485213875770569},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzzy.2005.1452416","is_oa":false,"landing_page_url":"http://doi.org/10.1109/fuzzy.2005.1452416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W282295065","https://openalex.org/W1529811231","https://openalex.org/W2108199536","https://openalex.org/W2108631315","https://openalex.org/W2115874005","https://openalex.org/W2118759915","https://openalex.org/W2132131403","https://openalex.org/W2150835122","https://openalex.org/W2156278464"],"related_works":["https://openalex.org/W3200817179","https://openalex.org/W1960166976","https://openalex.org/W2380067098","https://openalex.org/W1992708211","https://openalex.org/W1548152478","https://openalex.org/W2137172615","https://openalex.org/W2112564789","https://openalex.org/W2106247205","https://openalex.org/W3102386532","https://openalex.org/W4319872364"],"abstract_inverted_index":{"To":[0],"overcome":[1],"the":[2,38,44,64,67,81],"shortcomings":[3],"of":[4,11,34,40,46,66],"fully":[5,8],"analog":[6,41,54],"and":[7,43,84],"digital":[9,47],"implementation":[10,33,42],"artificial":[12],"neural":[13,68,82],"networks":[14,69],"(ANNs),":[15],"we":[16],"adopted":[17],"mixed":[18],"analog/digital":[19],"technique.":[20],"We":[21,49,62],"proposed":[22],"a":[23,28,52,58,86],"switched-resistor":[24,32],"(SR)":[25],"element":[26],"as":[27],"programmable":[29],"synapse.":[30],"The":[31,72],"synapse":[35],"captures":[36],"both":[37],"advantages":[39],"programmability":[45],"implementation.":[48],"also":[50],"designed":[51],"CMOS":[53],"neuron":[55],"that":[56,75],"performs":[57],"near-tanh":[59],"nonlinearity":[60],"function.":[61],"evaluated":[63],"performance":[65],"using":[70],"Pspice.":[71],"results":[73],"showed":[74],"our":[76],"approach":[77],"can":[78],"successfully":[79],"implement":[80],"network,":[83],"exhibit":[85],"very":[87],"high":[88],"modularity":[89]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
