{"id":"https://openalex.org/W3044327318","doi":"https://doi.org/10.1109/tnnls.2020.3008154","title":"A Hybrid CMOS-Memristive Approach to Designing Deep Generative Models","display_name":"A Hybrid CMOS-Memristive Approach to Designing Deep Generative Models","publication_year":2020,"publication_date":"2020-07-23","ids":{"openalex":"https://openalex.org/W3044327318","doi":"https://doi.org/10.1109/tnnls.2020.3008154","mag":"3044327318","pmid":"https://pubmed.ncbi.nlm.nih.gov/32701452"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.3008154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3008154","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5066176656","display_name":"Vivek Parmar","orcid":"https://orcid.org/0000-0001-7380-0816"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vivek Parmar","raw_affiliation_strings":["IIT Delhi, New Delhi, India"],"raw_orcid":"https://orcid.org/0000-0001-7380-0816","affiliations":[{"raw_affiliation_string":"IIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008011360","display_name":"Manan Suri","orcid":"https://orcid.org/0000-0003-1417-3570"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manan Suri","raw_affiliation_strings":["IIT Delhi, New Delhi, India"],"raw_orcid":"https://orcid.org/0000-0003-1417-3570","affiliations":[{"raw_affiliation_string":"IIT Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.3028,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.55654557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"32","issue":"6","first_page":"2790","last_page":"2796"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.814559817314148},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.7320928573608398},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6927400231361389},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6829079389572144},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.6722316741943359},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6690912246704102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6445004940032959},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5029768347740173},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5006470680236816},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.43149083852767944},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3926604390144348},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3470463752746582},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3436643183231354},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2620207965373993}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.814559817314148},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.7320928573608398},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6927400231361389},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6829079389572144},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.6722316741943359},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6690912246704102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6445004940032959},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5029768347740173},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5006470680236816},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.43149083852767944},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3926604390144348},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3470463752746582},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3436643183231354},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2620207965373993},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2020.3008154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3008154","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:32701452","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32701452","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2665857355","display_name":null,"funder_award_id":"CRG/2018/001901","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"}],"funders":[{"id":"https://openalex.org/F4320324473","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06"},{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W44815768","https://openalex.org/W1596035946","https://openalex.org/W1937359183","https://openalex.org/W1972477204","https://openalex.org/W1973445088","https://openalex.org/W1991059746","https://openalex.org/W2004823737","https://openalex.org/W2018774711","https://openalex.org/W2030671441","https://openalex.org/W2060694887","https://openalex.org/W2072128103","https://openalex.org/W2077586448","https://openalex.org/W2077751791","https://openalex.org/W2092462444","https://openalex.org/W2100495367","https://openalex.org/W2102409316","https://openalex.org/W2110798204","https://openalex.org/W2113038496","https://openalex.org/W2120432001","https://openalex.org/W2122221396","https://openalex.org/W2136922672","https://openalex.org/W2139427956","https://openalex.org/W2145094598","https://openalex.org/W2147010501","https://openalex.org/W2155377787","https://openalex.org/W2155954834","https://openalex.org/W2158164339","https://openalex.org/W2344162344","https://openalex.org/W2398563917","https://openalex.org/W2503374103","https://openalex.org/W2526812109","https://openalex.org/W2584311717","https://openalex.org/W2727914278","https://openalex.org/W2767048768","https://openalex.org/W2783393355","https://openalex.org/W2783915901","https://openalex.org/W2914410297","https://openalex.org/W2997574889","https://openalex.org/W3005885031","https://openalex.org/W3104135012","https://openalex.org/W4231109964","https://openalex.org/W4236126228","https://openalex.org/W6648322874","https://openalex.org/W6675401909","https://openalex.org/W6676481782","https://openalex.org/W6677208260","https://openalex.org/W6681096077","https://openalex.org/W6681934674","https://openalex.org/W6683128514"],"related_works":["https://openalex.org/W2128151361","https://openalex.org/W2999408031","https://openalex.org/W2902142523","https://openalex.org/W2064630666","https://openalex.org/W2287713958","https://openalex.org/W2291538051","https://openalex.org/W2133034788","https://openalex.org/W1257380361","https://openalex.org/W3005559199","https://openalex.org/W2790969636"],"abstract_inverted_index":{"Deep":[0],"learning":[1,26,169],"and":[2,13,81,104],"its":[3],"applications":[4],"have":[5,92],"gained":[6],"tremendous":[7],"interest":[8],"recently":[9],"in":[10,166,171],"both":[11,61],"academia":[12],"industry.":[14],"Restricted":[15],"Boltzmann":[16],"machines":[17],"(RBMs)":[18],"offer":[19,162],"a":[20,31,163],"key":[21],"methodology":[22],"to":[23],"implement":[24],"deep":[25,38,98],"paradigms.":[27],"This":[28],"brief":[29],"presents":[30],"novel":[32],"approach":[33],"for":[34,59,102,109,158],"realizing":[35,60],"hybrid":[36],"CMOS-memristive-based":[37],"generative":[39],"models":[40],"(DGMs).":[41],"In":[42],"our":[43],"proposed":[44,89,129,146,153],"DGM":[45],"architecture,":[46],"HfO":[47],"<sub":[48],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[49],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">x</sub>":[50],"-based":[51],"(filamentary-type":[52],"switching)":[53],"memristive":[54],"devices":[55],"are":[56,156],"extensively":[57],"used":[58,157],"computational":[62],"as":[63,65],"well":[64],"storage":[66],"functions,":[67],"such":[68],"as:":[69],"1)":[70,97],"synapses":[71],"(weights);":[72],"2)":[73,105],"internal":[74],"neuron-state":[75],"storage;":[76],"3)":[77],"stochastic":[78],"neuron":[79],"activation;":[80],"4)":[82],"programmable":[83],"signal":[84],"normalization.":[85],"To":[86],"validate":[87],"the":[88,110,116,128,134,145,152],"scheme,":[90],"we":[91],"simulated":[93],"two":[94],"different":[95],"architectures:":[96],"belief":[99],"network":[100,148],"(DBN)":[101],"classification":[103],"stacked":[106],"denoising":[107],"autoencoder":[108],"reconstruction":[111],"of":[112,127,144,168],"handwritten":[113],"digits":[114],"from":[115],"MNIST":[117],"data":[118],"set.":[119],"The":[120],"maximum":[121],"test":[122],"accuracy":[123],"achieved":[124,141],"by":[125,142],"pretraining":[126,143],"DBN":[130],"was":[131,149],"92.6%,":[132],"whereas":[133],"best":[135],"case":[136],"mean":[137],"squared":[138],"error":[139],"(mse)":[140],"SDA":[147],"0.046.":[150],"When":[151],"model-based":[154],"weights":[155],"weight":[159],"initialization,":[160],"they":[161],"significant":[164],"advantage":[165],"terms":[167],"performance":[170],"comparison":[172],"with":[173],"randomized":[174],"initialization.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}