{"id":"https://openalex.org/W2167963739","doi":"https://doi.org/10.1109/isqed.2009.4810354","title":"Kriging Model combined with latin hypercube sampling for surrogate modeling of analog integrated circuit performance","display_name":"Kriging Model combined with latin hypercube sampling for surrogate modeling of analog integrated circuit performance","publication_year":2009,"publication_date":"2009-03-01","ids":{"openalex":"https://openalex.org/W2167963739","doi":"https://doi.org/10.1109/isqed.2009.4810354","mag":"2167963739"},"language":"en","primary_location":{"id":"doi:10.1109/isqed.2009.4810354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed.2009.4810354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 10th International Symposium on Quality of Electronic Design","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/A5052123017","display_name":"Hailong You","orcid":"https://orcid.org/0000-0003-3427-5320"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hailong You","raw_affiliation_strings":["Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101191215","display_name":"Maofeng Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maofeng Yang","raw_affiliation_strings":["Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101593329","display_name":"Dan Wang","orcid":"https://orcid.org/0000-0002-4099-6004"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Wang","raw_affiliation_strings":["Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044290160","display_name":"Xinzhang Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinzhang Jia","raw_affiliation_strings":["Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Ministry of Education for Wide Band-Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5052123017"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":2.7422,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.90717045,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"554","last_page":"558"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9998999834060669,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/latin-hypercube-sampling","display_name":"Latin hypercube sampling","score":0.9587559700012207},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.8868544101715088},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.8086467981338501},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6966673731803894},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6223306655883789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5925471186637878},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3778536021709442},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3748937249183655},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34525877237319946},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.21761241555213928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21376708149909973},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18335270881652832},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15586385130882263},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12581709027290344}],"concepts":[{"id":"https://openalex.org/C20820323","wikidata":"https://www.wikidata.org/wiki/Q6496514","display_name":"Latin hypercube sampling","level":3,"score":0.9587559700012207},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.8868544101715088},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.8086467981338501},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6966673731803894},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6223306655883789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5925471186637878},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3778536021709442},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3748937249183655},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34525877237319946},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.21761241555213928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21376708149909973},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18335270881652832},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15586385130882263},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12581709027290344},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isqed.2009.4810354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed.2009.4810354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 10th International Symposium on Quality of Electronic Design","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":16,"referenced_works":["https://openalex.org/W48555456","https://openalex.org/W1695563742","https://openalex.org/W2006772343","https://openalex.org/W2018044188","https://openalex.org/W2024697317","https://openalex.org/W2044458183","https://openalex.org/W2110693389","https://openalex.org/W2135535501","https://openalex.org/W2144272793","https://openalex.org/W2153299515","https://openalex.org/W2483479423","https://openalex.org/W2599812937","https://openalex.org/W2611229919","https://openalex.org/W3124502797","https://openalex.org/W6735490388","https://openalex.org/W6737424570"],"related_works":["https://openalex.org/W3125613328","https://openalex.org/W2931365531","https://openalex.org/W3147153020","https://openalex.org/W3121339476","https://openalex.org/W2800575077","https://openalex.org/W3171168640","https://openalex.org/W3122455945","https://openalex.org/W3014573403","https://openalex.org/W2769797931","https://openalex.org/W4381941132"],"abstract_inverted_index":{"The":[0,137],"strong":[1],"nonlinearity":[2],"brought":[3],"by":[4],"the":[5,27,34,50,104,115,174],"large":[6],"circuit":[7,54,74,97,129,161,181],"scale":[8],"and":[9,38,102,114,123,147],"more":[10],"complicated":[11],"physical/electrical":[12],"models":[13],"is":[14],"making":[15],"traditional":[16,42,67,110],"response":[17,43,68,105,154],"surface":[18,44,69,106,155],"model":[19,45,70,86,95,142,156],"(i.e.":[20],"linear":[21],"or":[22,180],"quadratic":[23,153],"polynomial)":[24],"unsuitable":[25],"for":[26,41],"surrogate-modeling":[28,131],"of":[29,96,112,132,160,177],"nowadays":[30],"integrated":[31,134],"circuits.":[32],"Besides,":[33,170],"random-measurement-error-based":[35],"analysis":[36],"techniques":[37],"principles":[39],"developed":[40],"may":[46,172],"be":[47,164],"meaningless":[48],"facing":[49],"deterministic":[51],"data":[52],"from":[53],"simulation":[55],"experiments,":[56],"which":[57],"are":[58],"not":[59,72],"subject":[60],"to":[61,92,128,166],"random":[62],"measurement":[63],"errors":[64],"essentially.":[65],"Further,":[66],"can":[71,163],"mimic":[73],"behaviors":[75],"in":[76],"global":[77,175],"process/designable":[78],"parameter":[79],"space.":[80],"This":[81],"paper":[82],"proposes":[83],"using":[84],"Kriging":[85,116,141,158],"combined":[87,118],"with":[88,119],"Latin":[89,120],"hypercube":[90,121],"sampling":[91],"build":[93],"surrogate":[94],"performance.":[98,182],"We":[99],"firstly":[100],"introduce":[101],"compare":[103],"modeling":[107,117,159],"based":[108],"on":[109],"design":[111],"experiments":[113],"sampling,":[122],"then":[124],"apply":[125],"both":[126],"methods":[127],"performance":[130,162],"an":[133],"operational":[135],"amplifier.":[136],"result":[138],"shows":[139],"that":[140],"needs":[143],"less":[144],"sample":[145],"points":[146],"provides":[148],"2times":[149],"higher":[150],"accuracy":[151],"than":[152],"does.":[157],"utilized":[165],"estimate":[167],"parametric":[168,178],"yield.":[169],"it":[171],"facilitate":[173],"optimization":[176],"yield":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
