{"id":"https://openalex.org/W2996969031","doi":"https://doi.org/10.1109/iccad45719.2019.8942069","title":"Efficient Yield Analysis for SRAM and Analog Circuits using Meta-Model based Importance Sampling Method","display_name":"Efficient Yield Analysis for SRAM and Analog Circuits using Meta-Model based Importance Sampling Method","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2996969031","doi":"https://doi.org/10.1109/iccad45719.2019.8942069","mag":"2996969031"},"language":"en","primary_location":{"id":"doi:10.1109/iccad45719.2019.8942069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad45719.2019.8942069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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":null,"display_name":"Xiao Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Shi","raw_affiliation_strings":["State Key Lab of ASIC & System Fudan University,Microelectronics Dept.,China"],"affiliations":[{"raw_affiliation_string":"State Key Lab of ASIC & System Fudan University,Microelectronics Dept.,China","institution_ids":["https://openalex.org/I4210132426","https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040139371","display_name":"Hao Yan","orcid":"https://orcid.org/0000-0002-5312-4483"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Yan","raw_affiliation_strings":["Southeast University,Electrical Engineering Dept.,China"],"affiliations":[{"raw_affiliation_string":"Southeast University,Electrical Engineering Dept.,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101731389","display_name":"Jiajia Zhang","orcid":"https://orcid.org/0009-0009-9813-8895"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajia Zhang","raw_affiliation_strings":["Southeast University,Electrical Engineering Dept.,China"],"affiliations":[{"raw_affiliation_string":"Southeast University,Electrical Engineering Dept.,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058632983","display_name":"Qiancun Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiancun Huang","raw_affiliation_strings":["Southeast University,Electrical Engineering Dept.,China"],"affiliations":[{"raw_affiliation_string":"Southeast University,Electrical Engineering Dept.,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101499715","display_name":"Longxing Shi","orcid":"https://orcid.org/0000-0002-0629-7154"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longxing Shi","raw_affiliation_strings":["Southeast University,Electrical Engineering Dept.,China"],"affiliations":[{"raw_affiliation_string":"Southeast University,Electrical Engineering Dept.,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008695429","display_name":"Lei He","orcid":"https://orcid.org/0000-0002-5266-3805"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei He","raw_affiliation_strings":["University of California,Electrical and Computer Engineering Dept.,Los Angeles,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Electrical and Computer Engineering Dept.,Los Angeles,CA,USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067","https://openalex.org/I4210132426"],"apc_list":null,"apc_paid":null,"fwci":0.166,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6397302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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"}},{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9980000257492065,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.995199978351593,"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/computer-science","display_name":"Computer science","score":0.6442229151725769},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.6088189482688904},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.5675796866416931},{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.5439415574073792},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5416702628135681},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5298946499824524},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5098761320114136},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4936927258968353},{"id":"https://openalex.org/keywords/slice-sampling","display_name":"Slice sampling","score":0.47146350145339966},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.41620564460754395},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41206568479537964},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4113466143608093},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.34960776567459106},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3268822133541107},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24018463492393494},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2083360254764557},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13471221923828125}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6442229151725769},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.6088189482688904},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.5675796866416931},{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.5439415574073792},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5416702628135681},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5298946499824524},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5098761320114136},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4936927258968353},{"id":"https://openalex.org/C170593435","wikidata":"https://www.wikidata.org/wiki/Q4128565","display_name":"Slice sampling","level":4,"score":0.47146350145339966},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.41620564460754395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41206568479537964},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4113466143608093},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.34960776567459106},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3268822133541107},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24018463492393494},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2083360254764557},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13471221923828125},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/iccad45719.2019.8942069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad45719.2019.8942069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1979969656","https://openalex.org/W2018044188","https://openalex.org/W2033246483","https://openalex.org/W2083782718","https://openalex.org/W2103793078","https://openalex.org/W2119312496","https://openalex.org/W2120353978","https://openalex.org/W2129905273","https://openalex.org/W2158683023","https://openalex.org/W2329870304","https://openalex.org/W2465616027","https://openalex.org/W2519965010","https://openalex.org/W2809533575"],"related_works":["https://openalex.org/W3047994252","https://openalex.org/W2592308920","https://openalex.org/W4300460000","https://openalex.org/W2142819099","https://openalex.org/W3132384579","https://openalex.org/W769381313","https://openalex.org/W2736517747","https://openalex.org/W2049791232","https://openalex.org/W2766819726","https://openalex.org/W4287691656"],"abstract_inverted_index":{"Performance":[0],"failure":[1,27,37,104,128,146],"has":[2],"become":[3],"the":[4,8,24,76],"major":[5],"threat":[6],"to":[7,21,57,71,92,117,143],"robustness":[9],"and":[10,15,63,95,111],"reliability":[11],"of":[12],"various":[13],"memory":[14],"analog":[16],"circuits.":[17],"It":[18],"is":[19,131],"challenging":[20],"accurately":[22],"estimate":[23],"extremely":[25],"small":[26],"probability":[28],"when":[29,115],"failed":[30],"samples":[31,74,110],"are":[32],"distributed":[33],"in":[34,86,148],"multiple":[35,127],"disjoint":[36],"regions.":[38],"In":[39],"this":[40],"paper,":[41],"we":[42],"develop":[43],"a":[44,122],"novel":[45],"meta-model":[46,56],"based":[47],"importance":[48,60],"sampling":[49,61],"(MIS)":[50],"method.":[51],"MIS":[52,90,106,130],"utilizes":[53],"Gaussian":[54],"Process":[55],"construct":[58],"quasi-optimal":[59],"distribution,":[62],"performs":[64],"Markov":[65],"Chain":[66],"Monte":[67],"Carlo":[68],"(MCMC)":[69],"simulation":[70],"generate":[72],"new":[73],"from":[75],"proposed":[77],"distribution.":[78],"By":[79],"updating":[80],"our":[81,149],"global":[82],"Importance":[83],"Sampling":[84],"estimator":[85],"an":[87],"iterated":[88],"framework,":[89],"leads":[91],"better":[93,113],"efficiency":[94],"higher":[96],"accuracy.":[97],"For":[98,121],"SRAM":[99],"bit":[100],"cell":[101],"with":[102,126],"single":[103],"region,":[105],"uses":[107],"4-6X":[108],"fewer":[109],"reaches":[112],"accuracy":[114],"compared":[116],"several":[118],"recent":[119],"methods.":[120],"two-stage":[123],"amplifier":[124],"circuit":[125],"schemes,":[129],"213X":[132],"faster":[133],"than":[134],"MC":[135],"without":[136],"compromising":[137],"accuracy,":[138],"while":[139],"other":[140],"methods":[141],"fail":[142],"cover":[144],"all":[145],"regions":[147],"experiment.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
