{"id":"https://openalex.org/W2038556747","doi":"https://doi.org/10.1515/mcma-2013-0004","title":"An algorithm for on-the-fly generation of samples of non-stationary Gaussian processes based on a sampling theorem","display_name":"An algorithm for on-the-fly generation of samples of non-stationary Gaussian processes based on a sampling theorem","publication_year":2013,"publication_date":"2013-01-05","ids":{"openalex":"https://openalex.org/W2038556747","doi":"https://doi.org/10.1515/mcma-2013-0004","mag":"2038556747"},"language":"en","primary_location":{"id":"doi:10.1515/mcma-2013-0004","is_oa":false,"landing_page_url":"http://doi.org/10.1515/mcma-2013-0004","pdf_url":null,"source":{"id":"https://openalex.org/S142132501","display_name":"Monte Carlo Methods and Applications","issn_l":"0929-9629","issn":["0929-9629","1569-3961"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Monte Carlo Methods and Applications","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/A5103002453","display_name":"Richard Field","orcid":"https://orcid.org/0000-0002-2765-7032"},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Richard V. Field, Jr.","raw_affiliation_strings":["Sandia National Laboratories, Albuquerque, NM 87185-0346, USA"],"affiliations":[{"raw_affiliation_string":"Sandia National Laboratories, Albuquerque, NM 87185-0346, USA","institution_ids":["https://openalex.org/I4210104735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103482716","display_name":"Mircea Grigoriu","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mircea Grigoriu","raw_affiliation_strings":["Cornell University, Ithaca, NY 14853, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY 14853, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036660014","display_name":"Clark R. Dohrmann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Clark R. Dohrmann","raw_affiliation_strings":["Sandia National Laboratories, Albuquerque, NM 87185-0346, USA"],"affiliations":[{"raw_affiliation_string":"Sandia National Laboratories, Albuquerque, NM 87185-0346, USA","institution_ids":["https://openalex.org/I4210104735"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103002453"],"corresponding_institution_ids":["https://openalex.org/I4210104735"],"apc_list":null,"apc_paid":null,"fwci":0.4829,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64029812,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"0","issue":"0","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.9036999940872192,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.9036999940872192,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6459367275238037},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6317564845085144},{"id":"https://openalex.org/keywords/rejection-sampling","display_name":"Rejection sampling","score":0.533616304397583},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5164347290992737},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5137695074081421},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5129387378692627},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4796783924102783},{"id":"https://openalex.org/keywords/monte-carlo-integration","display_name":"Monte Carlo integration","score":0.4351285398006439},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42821845412254333},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4256821870803833},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.41897502541542053},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.36719536781311035},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36314189434051514},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.26926761865615845},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1723000407218933},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.1489073634147644}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6459367275238037},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6317564845085144},{"id":"https://openalex.org/C187192777","wikidata":"https://www.wikidata.org/wiki/Q381699","display_name":"Rejection sampling","level":5,"score":0.533616304397583},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5164347290992737},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5137695074081421},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5129387378692627},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4796783924102783},{"id":"https://openalex.org/C132725507","wikidata":"https://www.wikidata.org/wiki/Q39879","display_name":"Monte Carlo integration","level":5,"score":0.4351285398006439},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42821845412254333},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4256821870803833},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.41897502541542053},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.36719536781311035},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36314189434051514},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.26926761865615845},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1723000407218933},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.1489073634147644},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1515/mcma-2013-0004","is_oa":false,"landing_page_url":"http://doi.org/10.1515/mcma-2013-0004","pdf_url":null,"source":{"id":"https://openalex.org/S142132501","display_name":"Monte Carlo Methods and Applications","issn_l":"0929-9629","issn":["0929-9629","1569-3961"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Monte Carlo Methods and Applications","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:bpj:mcmeap:v:19:y:2013:i:2:p:143-169:n:1","is_oa":false,"landing_page_url":"https://doi.org/10.1515/mcma-2013-0004","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2053391762","https://openalex.org/W2127292590","https://openalex.org/W2056024200","https://openalex.org/W133978387","https://openalex.org/W2055661359","https://openalex.org/W1981576072","https://openalex.org/W3105263408","https://openalex.org/W7382088","https://openalex.org/W2025863411","https://openalex.org/W2128088998","https://openalex.org/W2053098517","https://openalex.org/W2074882046","https://openalex.org/W2123594237","https://openalex.org/W2080328084","https://openalex.org/W2052920959","https://openalex.org/W2852782812","https://openalex.org/W2165288561","https://openalex.org/W3015274040","https://openalex.org/W192652410","https://openalex.org/W2115491369"],"abstract_inverted_index":{"A":[0],"Monte":[1,112],"Carlo":[2,113],"algorithm":[3,35,60],"is":[4,16,47,55],"developed":[5],"for":[6,26,36,49,85],"generating":[7,37],"samples":[8],"of":[9,22,43,58,70,73,88,109],"real-valued":[10],"non-stationary":[11],"Gaussian":[12,39],"processes.":[13],"The":[14],"method":[15,45],"based":[17],"on":[18],"a":[19],"generalized":[20],"version":[21],"Shannon's":[23],"sampling":[24],"theorem":[25],"bandlimited":[27],"deterministic":[28],"signals,":[29],"as":[30,32],"well":[31],"an":[33],"efficient":[34],"conditional":[38],"variables.":[40],"One":[41],"feature":[42],"the":[44,56,59,68,71,74,77,83,86,89,92,104,110],"that":[46],"attractive":[48],"engineering":[50],"applications":[51],"involving":[52],"stochastic":[53],"loads":[54],"ability":[57],"to":[61],"be":[62],"implemented":[63],"\u201con-the-fly\u201d":[64],"meaning":[65],"that,":[66],"given":[67],"value":[69,84],"sample":[72,87],"process":[75,90],"at":[76,91],"current":[78],"time":[79,94],"step,":[80],"it":[81],"provides":[82],"next":[93],"step.":[95],"Theoretical":[96],"arguments":[97],"are":[98],"supported":[99],"by":[100],"numerical":[101],"examples":[102],"demonstrating":[103],"implementation,":[105],"efficiency,":[106],"and":[107],"accuracy":[108],"proposed":[111],"simulation":[114],"algorithm.":[115]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}