{"id":"https://openalex.org/W2919730780","doi":"https://doi.org/10.1109/acssc.2018.8645359","title":"Explorations of Temporal Causality Using Partial Coherence","display_name":"Explorations of Temporal Causality Using Partial Coherence","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2919730780","doi":"https://doi.org/10.1109/acssc.2018.8645359","mag":"2919730780"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2018.8645359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2018.8645359","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"},"type":"conference-paper","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/A5080469112","display_name":"Louis L. Scharf","orcid":"https://orcid.org/0000-0003-1764-9335"},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Louis Scharf","raw_affiliation_strings":["Departments of Mathematics and Statistics, Colorado State University, Fort Collins, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departments of Mathematics and Statistics, Colorado State University, Fort Collins, CO, USA","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100344901","display_name":"Yuan Wang","orcid":"https://orcid.org/0000-0003-2629-4572"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan Wang","raw_affiliation_strings":["Department of Mathematics and Statistics, Washington State University, Pullman, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Washington State University, Pullman, WA, USA","institution_ids":["https://openalex.org/I72951846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"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":"1767","last_page":"1771"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9896000027656555,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9896000027656555,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.6781725287437439},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.6574211120605469},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.520969033241272},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4739917516708374},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.45716559886932373},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4290677011013031},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.41104716062545776},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39929527044296265},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3479083180427551},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2846373915672302},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24480211734771729},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11727982759475708},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.09169772267341614}],"concepts":[{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.6781725287437439},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.6574211120605469},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.520969033241272},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4739917516708374},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.45716559886932373},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4290677011013031},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.41104716062545776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39929527044296265},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3479083180427551},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2846373915672302},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24480211734771729},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11727982759475708},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.09169772267341614},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2018.8645359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2018.8645359","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1607114662","https://openalex.org/W2025371899","https://openalex.org/W2050523241","https://openalex.org/W2066400502","https://openalex.org/W2079656335","https://openalex.org/W2101668146","https://openalex.org/W2167826316","https://openalex.org/W2178225550","https://openalex.org/W2800659363","https://openalex.org/W2805426804","https://openalex.org/W4231726431","https://openalex.org/W4232900769"],"related_works":["https://openalex.org/W2081494945","https://openalex.org/W2389053294","https://openalex.org/W2359776416","https://openalex.org/W1970893504","https://openalex.org/W4312071518","https://openalex.org/W2901208600","https://openalex.org/W1677090476","https://openalex.org/W2886934452","https://openalex.org/W1489099099","https://openalex.org/W2024369332"],"abstract_inverted_index":{"In":[0],"this":[1,40],"paper":[2],"we":[3],"explore":[4],"partial":[5,33,47,91],"coherence":[6,34,48,60,92],"as":[7],"a":[8,30,45,66,74],"tool":[9],"for":[10],"evaluating":[11],"the":[12,54,82,88,94],"causal,":[13],"anti-causal":[14],"or":[15,78],"mixed-causal":[16],"dependence":[17],"of":[18,37,56,90,96],"one":[19],"time":[20],"series":[21],"on":[22],"another.":[23],"The":[24],"key":[25],"idea":[26],"is":[27,42,50,62],"to":[28,52,64,93],"establish":[29],"connection":[31,41],"between":[32],"and":[35],"questions":[36],"causality.":[38,58,98],"Once":[39],"established,":[43],"then":[44],"scale-invariant":[46],"statistic":[49,61],"used":[51],"resolve":[53],"question":[55],"temporal":[57,97],"This":[59],"shown":[63],"be":[65,71],"likelihood":[67],"ratio.":[68],"It":[69],"may":[70],"computed":[72],"from":[73,79],"composite":[75],"covariance":[76],"matrix":[77],"its":[80],"inverse,":[81],"information":[83],"matrix.":[84],"Numerical":[85],"experiments":[86],"demonstrate":[87],"application":[89],"resolution":[95]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
