{"id":"https://openalex.org/W4415706999","doi":"https://doi.org/10.1109/tcsii.2025.3627078","title":"Computing Max 3-Cut With CMOS Tripolar Oscillatory Cellular Neural Networks","display_name":"Computing Max 3-Cut With CMOS Tripolar Oscillatory Cellular Neural Networks","publication_year":2025,"publication_date":"2025-10-30","ids":{"openalex":"https://openalex.org/W4415706999","doi":"https://doi.org/10.1109/tcsii.2025.3627078"},"language":null,"primary_location":{"id":"doi:10.1109/tcsii.2025.3627078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsii.2025.3627078","pdf_url":null,"source":{"id":"https://openalex.org/S93916849","display_name":"IEEE Transactions on Circuits & Systems II Express Briefs","issn_l":"1549-7747","issn":["1549-7747","1558-3791"],"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 Circuits and Systems II: Express Briefs","raw_type":"journal-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/A5058384810","display_name":"Richelle L. Smith","orcid":"https://orcid.org/0000-0001-7370-9609"},"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"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Richelle L. Smith","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102823919","display_name":"Thomas H. Lee","orcid":"https://orcid.org/0000-0003-0635-2990"},"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"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas H. Lee","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058384810"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3917124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"72","issue":"12","first_page":"2032","last_page":"2036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11347","display_name":"Neural Networks Stability and Synchronization","score":0.9301999807357788,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11347","display_name":"Neural Networks Stability and Synchronization","score":0.9301999807357788,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13182","display_name":"Quantum-Dot Cellular Automata","score":0.0142000000923872,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.010599999688565731,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5343999862670898},{"id":"https://openalex.org/keywords/impulse","display_name":"Impulse (physics)","score":0.5236999988555908},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.4828000068664551},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46000000834465027},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.41679999232292175},{"id":"https://openalex.org/keywords/cellular-neural-network","display_name":"Cellular neural network","score":0.4000000059604645},{"id":"https://openalex.org/keywords/hamiltonian","display_name":"Hamiltonian (control theory)","score":0.38350000977516174},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.3621000051498413}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5773000121116638},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5343999862670898},{"id":"https://openalex.org/C70836080","wikidata":"https://www.wikidata.org/wiki/Q837940","display_name":"Impulse (physics)","level":2,"score":0.5236999988555908},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.4828000068664551},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46000000834465027},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.41679999232292175},{"id":"https://openalex.org/C812465","wikidata":"https://www.wikidata.org/wiki/Q5058375","display_name":"Cellular neural network","level":3,"score":0.4000000059604645},{"id":"https://openalex.org/C130787639","wikidata":"https://www.wikidata.org/wiki/Q5645293","display_name":"Hamiltonian (control theory)","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.3621000051498413},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.35350000858306885},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C187455244","wikidata":"https://www.wikidata.org/wiki/Q942353","display_name":"Boolean function","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C190560348","wikidata":"https://www.wikidata.org/wiki/Q3245116","display_name":"Circuit design","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C98925819","wikidata":"https://www.wikidata.org/wiki/Q7235385","display_name":"Potts model","level":3,"score":0.3160000145435333},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31439998745918274},{"id":"https://openalex.org/C8171440","wikidata":"https://www.wikidata.org/wiki/Q903414","display_name":"Steady state (chemistry)","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2953999936580658},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.2883000075817108},{"id":"https://openalex.org/C72279823","wikidata":"https://www.wikidata.org/wiki/Q1139726","display_name":"Impulse response","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2856000065803528},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.2646999955177307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsii.2025.3627078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsii.2025.3627078","pdf_url":null,"source":{"id":"https://openalex.org/S93916849","display_name":"IEEE Transactions on Circuits & Systems II Express Briefs","issn_l":"1549-7747","issn":["1549-7747","1558-3791"],"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 Circuits and Systems II: Express Briefs","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1550845590","https://openalex.org/W1965511886","https://openalex.org/W1980949197","https://openalex.org/W1994932713","https://openalex.org/W2056717940","https://openalex.org/W2104340505","https://openalex.org/W2108044931","https://openalex.org/W2140498717","https://openalex.org/W2160121923","https://openalex.org/W2806136642","https://openalex.org/W2954555660","https://openalex.org/W2960011723","https://openalex.org/W2997883506","https://openalex.org/W3014291826","https://openalex.org/W3216971543","https://openalex.org/W4205172069","https://openalex.org/W4205585032","https://openalex.org/W4225291083","https://openalex.org/W4360993037","https://openalex.org/W4396606037","https://openalex.org/W4396712855"],"related_works":[],"abstract_inverted_index":{"This":[0],"brief":[1],"presents":[2],"an":[3,124],"approach":[4],"to":[5,20,35,93,106],"solve":[6],"Max":[7,21,78,129],"3-Cut":[8,22,79],"problems":[9],"using":[10,40,97,114],"tripolar":[11,71],"oscillatory":[12],"cellular":[13],"neural":[14],"networks.":[15],"We":[16,33,50,67,88,101],"demonstrate":[17],"the":[18,30,37,52,57,77,108,139],"solution":[19,55],"can":[23],"be":[24],"formulated":[25],"in":[26,127,135],"terms":[27],"of":[28,43,56,80,110,117],"minimizing":[29],"Potts":[31,38],"Hamiltonian.":[32],"propose":[34],"minimize":[36],"Hamiltonian":[39],"a":[41,69,81,90,115],"network":[42,59,73,112],"connected":[44],"oscillators":[45],"under":[46],"divide-by-3":[47],"injection":[48],"locking.":[49],"derive":[51],"steady":[53],"state":[54],"oscillator":[58,72],"by":[60],"applying":[61],"impulse":[62],"sensitivity":[63],"function":[64],"(ISF)":[65],"theory.":[66],"design":[68],"CMOS":[70],"circuit":[74,92,105],"for":[75],"computing":[76,128],"triforce":[82],"graph":[83],"(first-order":[84],"Sierpi\u0144ski":[85],"triangle":[86],"graph).":[87],"develop":[89],"second":[91],"perform":[94],"image":[95],"segmentation,":[96],"signed":[98,118],"(positive/negative)":[99],"couplings.":[100],"then":[102],"extend":[103],"our":[104],"simulate":[107],"dynamics":[109],"social":[111],"alliances,":[113],"combination":[116],"and":[119],"weighted":[120],"couplings":[121],"that":[122],"play":[123],"essential":[125],"role":[126],"3-Cut.":[130],"Spectre":[131],"simulation":[132],"results":[133],"are":[134],"good":[136],"agreement":[137],"with":[138],"theoretical":[140],"analysis.":[141]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-30T00:00:00"}
