{"id":"https://openalex.org/W2285037406","doi":"https://doi.org/10.5353/th_b5194742","title":"Efficient circuit simulation via adaptive moment matching and matrix exponential techniques","display_name":"Efficient circuit simulation via adaptive moment matching and matrix exponential techniques","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2285037406","doi":"https://doi.org/10.5353/th_b5194742","mag":"2285037406"},"language":"en","primary_location":{"id":"doi:10.5353/th_b5194742","is_oa":true,"landing_page_url":"https://doi.org/10.5353/th_b5194742","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The University of Hong Kong","raw_type":"dissertation"},"type":"dissertation","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5353/th_b5194742","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101840504","display_name":"Wenhui Zhao","orcid":"https://orcid.org/0000-0002-2635-4814"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wenhui Zhao","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101840504"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11416","display_name":"Numerical methods for differential equations","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10792","display_name":"Matrix Theory and Algorithms","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.6987395286560059},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5607460141181946},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.551501989364624},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5215118527412415},{"id":"https://openalex.org/keywords/very-large-scale-integration","display_name":"Very-large-scale integration","score":0.48121121525764465},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4624808728694916},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.44693076610565186},{"id":"https://openalex.org/keywords/model-order-reduction","display_name":"Model order reduction","score":0.42422330379486084},{"id":"https://openalex.org/keywords/floating-point","display_name":"Floating point","score":0.41911616921424866},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3619083762168884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32615426182746887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.148975670337677}],"concepts":[{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.6987395286560059},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5607460141181946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.551501989364624},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5215118527412415},{"id":"https://openalex.org/C14580979","wikidata":"https://www.wikidata.org/wiki/Q876049","display_name":"Very-large-scale integration","level":2,"score":0.48121121525764465},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4624808728694916},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.44693076610565186},{"id":"https://openalex.org/C2779277453","wikidata":"https://www.wikidata.org/wiki/Q12202921","display_name":"Model order reduction","level":3,"score":0.42422330379486084},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.41911616921424866},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3619083762168884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32615426182746887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.148975670337677},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5353/th_b5194742","is_oa":true,"landing_page_url":"https://doi.org/10.5353/th_b5194742","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The University of Hong Kong","raw_type":"dissertation"},{"id":"pmh:oai:hub.hku.hk:10722/197488","is_oa":true,"landing_page_url":"http://hdl.handle.net/10722/197488","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"PG_Thesis"}],"best_oa_location":{"id":"doi:10.5353/th_b5194742","is_oa":true,"landing_page_url":"https://doi.org/10.5353/th_b5194742","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The University of Hong Kong","raw_type":"dissertation"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1497396554","https://openalex.org/W1506342804","https://openalex.org/W1520511539","https://openalex.org/W1551480811","https://openalex.org/W1552548571","https://openalex.org/W1556851660","https://openalex.org/W1968323692","https://openalex.org/W1969337756","https://openalex.org/W1978115611","https://openalex.org/W1980357388","https://openalex.org/W1980431326","https://openalex.org/W1983444632","https://openalex.org/W1984347942","https://openalex.org/W1996297482","https://openalex.org/W2001988116","https://openalex.org/W2012374408","https://openalex.org/W2013912476","https://openalex.org/W2022615414","https://openalex.org/W2028948789","https://openalex.org/W2032919707","https://openalex.org/W2039167131","https://openalex.org/W2040579262","https://openalex.org/W2052604766","https://openalex.org/W2055891331","https://openalex.org/W2057602562","https://openalex.org/W2064733273","https://openalex.org/W2067136705","https://openalex.org/W2079063703","https://openalex.org/W2089009503","https://openalex.org/W2098502158","https://openalex.org/W2100209300","https://openalex.org/W2103960654","https://openalex.org/W2107005953","https://openalex.org/W2115595920","https://openalex.org/W2118076222","https://openalex.org/W2119695238","https://openalex.org/W2119853749","https://openalex.org/W2121634787","https://openalex.org/W2122608783","https://openalex.org/W2123947147","https://openalex.org/W2126903321","https://openalex.org/W2128919817","https://openalex.org/W2134690279","https://openalex.org/W2136556155","https://openalex.org/W2139030761","https://openalex.org/W2147085805","https://openalex.org/W2170746497","https://openalex.org/W2963747658"],"related_works":["https://openalex.org/W4283025278","https://openalex.org/W61292821","https://openalex.org/W2082432309","https://openalex.org/W817174743","https://openalex.org/W2050492524","https://openalex.org/W2998315020","https://openalex.org/W2104790384","https://openalex.org/W1976665945","https://openalex.org/W3016208414","https://openalex.org/W2161271931"],"abstract_inverted_index":{"This":[0],"dissertation":[1],"presents":[2],"two":[3],"efficient":[4,297],"circuit":[5,25,209],"simulation":[6,26,53,210,233],"techniques":[7],"for":[8,77,131,208,231,249,299,320],"very":[9],"large":[10],"scale":[11],"integrated":[12],"(VLSI)":[13],"circuits.":[14,236],"Model":[15],"order":[16,45,82,149],"reduction":[17],"(MOR)":[18],"plays":[19],"a":[20,90,123,153,159,171,189,198,228,303],"significant":[21],"role":[22],"in":[23,89,113,212,317],"VLSI":[24,235],"as":[27],"nowadays":[28],"the":[29,44,47,52,74,80,96,100,163,166,216,238,253,260,265,270,278,286,318,330,337,340],"system":[30,49,164,266],"model":[31,102],"may":[32],"contain":[33],"millions":[34],"of":[35,46,61,73,99,133,162,234,240,264,288],"equations":[36],"or":[37],"variables.":[38],"MOR":[39,132],"is":[40,71,106,194,215,247,275],"needed":[41],"to":[42,50,54,108,170,226,258,277,292,335],"reduce":[43],"original":[48],"allow":[51],"be":[55,227],"performed":[56],"with":[57,177],"an":[58,110,325],"acceptable":[59],"amount":[60],"time,":[62],"reasonable":[63],"storage":[64],"and":[65,83,146,296,314,323,342],"reliable":[66],"accuracy.":[67,280],"Multi-point":[68],"moment":[69,81,116,128,148,180],"matching":[70,129,181],"one":[72],"state-of-the-art":[75],"methods":[76],"MOR.":[78],"However,":[79],"expansion":[84,143],"points":[85],"are":[86,186],"usually":[87],"selected":[88],"heuristic":[91],"way,":[92],"which":[93,193],"cannot":[94],"guarantee":[95],"global":[97,174],"accuracy":[98,175],"reduced-order":[101],"(ROM).":[103],"Therefore,":[104],"it":[105],"important":[107,276],"utilize":[109],"adaptive":[111,126,141,326],"algorithm":[112,130,138,168],"exercising":[114],"multi-point":[115,127],"matching.":[117],"In":[118,281],"this":[119,213,282],"regard,":[120],"we":[121,284],"propose":[122,324],"novel":[124],"automatic":[125,147],"linear":[134],"descriptor":[135],"systems.":[136],"The":[137,184],"implements":[139],"both":[140],"frequency":[142],"point":[144],"selection":[145],"control":[150],"guided":[151],"by":[152,197],"transfer":[154],"function-based":[155],"error":[156],"metric.":[157],"Without":[158],"priori":[160],"information":[161],"response,":[165],"proposed":[167,200,211],"leads":[169],"much":[172],"higher":[173],"compared":[176],"standard":[178],"multipoint":[179],"without":[182],"adaptation.":[183],"moments":[185],"computed":[187],"via":[188],"generalized":[190,201,306,331],"Sylvester":[191],"equation":[192],"subsequently":[195],"solved":[196],"newly":[199],"alternating":[202],"direction":[203],"implicit":[204],"(GADI)":[205],"method.&#13;\\n&#13;\\nAnother":[206],"technique":[207],"thesis":[214],"matrix":[217],"exponential":[218],"(MEXP)":[219],"method.":[220],"MEXP":[221,241],"method":[222],"has":[223],"been":[224],"demonstrated":[225],"competitive":[229],"candidate":[230],"transient":[232],"Nevertheless,":[237],"performance":[239],"based":[242,328],"on":[243,329],"ordinary":[244],"Krylov":[245,290,308,333],"subspace":[246,291,319,334],"unsatisfactory":[248],"stiff":[250],"circuits,":[251],"because":[252],"underlying":[254],"Arnoldi":[255],"process":[256],"tends":[257],"oversample":[259],"high":[261],"magnitude":[262,272],"part":[263,273],"spectrum":[267],"while":[268],"under-sampling":[269],"low":[271],"that":[274,310],"final":[279],"thesis,":[283],"explore":[285],"use":[287],"extended":[289,307,332],"generate":[293],"more":[294],"accurate":[295],"approximation":[298],"MEXP.We":[300],"also":[301],"develop":[302],"formulation,":[304],"called":[305],"subspace,":[309],"allows":[311],"unequal":[312],"positive":[313,341],"negative":[315,343],"dimensions":[316],"better":[321],"performance,":[322],"scheme":[327],"select":[336],"ratio":[338],"between":[339],"dimensions.":[344]},"counts_by_year":[],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
