{"id":"https://openalex.org/W3015446420","doi":"https://doi.org/10.1109/icassp40776.2020.9054388","title":"Multitaper Spectral Granger Causality with Application to Ssvep","display_name":"Multitaper Spectral Granger Causality with Application to Ssvep","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015446420","doi":"https://doi.org/10.1109/icassp40776.2020.9054388","mag":"3015446420"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5038023750","display_name":"Rachele Anderson","orcid":"https://orcid.org/0000-0002-5871-8192"},"institutions":[{"id":"https://openalex.org/I1279596006","display_name":"Statistics Sweden","ror":"https://ror.org/05x7wz523","country_code":"SE","type":"government","lineage":["https://openalex.org/I1279596006"]},{"id":"https://openalex.org/I187531555","display_name":"Lund University","ror":"https://ror.org/012a77v79","country_code":"SE","type":"education","lineage":["https://openalex.org/I187531555"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Rachele Anderson","raw_affiliation_strings":["Mathematical Statistics, Centre for Mathematical Sciences, Lund University, Sweden"],"affiliations":[{"raw_affiliation_string":"Mathematical Statistics, Centre for Mathematical Sciences, Lund University, Sweden","institution_ids":["https://openalex.org/I1279596006","https://openalex.org/I187531555"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040600213","display_name":"Maria Sandsten","orcid":"https://orcid.org/0000-0002-8117-9588"},"institutions":[{"id":"https://openalex.org/I187531555","display_name":"Lund University","ror":"https://ror.org/012a77v79","country_code":"SE","type":"education","lineage":["https://openalex.org/I187531555"]},{"id":"https://openalex.org/I1279596006","display_name":"Statistics Sweden","ror":"https://ror.org/05x7wz523","country_code":"SE","type":"government","lineage":["https://openalex.org/I1279596006"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Maria Sandsten","raw_affiliation_strings":["Mathematical Statistics, Centre for Mathematical Sciences, Lund University, Sweden"],"affiliations":[{"raw_affiliation_string":"Mathematical Statistics, Centre for Mathematical Sciences, Lund University, Sweden","institution_ids":["https://openalex.org/I1279596006","https://openalex.org/I187531555"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038023750"],"corresponding_institution_ids":["https://openalex.org/I1279596006","https://openalex.org/I187531555"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03187306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":null,"first_page":"1284","last_page":"1288"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.998199999332428,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multitaper","display_name":"Multitaper","score":0.9854772090911865},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7708856463432312},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7513617277145386},{"id":"https://openalex.org/keywords/bispectrum","display_name":"Bispectrum","score":0.5915480852127075},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5741863250732422},{"id":"https://openalex.org/keywords/granger-causality","display_name":"Granger causality","score":0.5355501174926758},{"id":"https://openalex.org/keywords/spectral-density-estimation","display_name":"Spectral density estimation","score":0.5238247513771057},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5141506791114807},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.45907044410705566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4569045603275299},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4457736313343048},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37068089842796326},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34721431136131287},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3251676559448242},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29494011402130127},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2886863946914673},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.2615565061569214},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.13573119044303894},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08026584982872009}],"concepts":[{"id":"https://openalex.org/C2777067715","wikidata":"https://www.wikidata.org/wiki/Q3327726","display_name":"Multitaper","level":2,"score":0.9854772090911865},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7708856463432312},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7513617277145386},{"id":"https://openalex.org/C114148568","wikidata":"https://www.wikidata.org/wiki/Q2410583","display_name":"Bispectrum","level":3,"score":0.5915480852127075},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5741863250732422},{"id":"https://openalex.org/C129824826","wikidata":"https://www.wikidata.org/wiki/Q2630107","display_name":"Granger causality","level":2,"score":0.5355501174926758},{"id":"https://openalex.org/C30049272","wikidata":"https://www.wikidata.org/wiki/Q6555326","display_name":"Spectral density estimation","level":3,"score":0.5238247513771057},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5141506791114807},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.45907044410705566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4569045603275299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4457736313343048},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37068089842796326},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34721431136131287},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3251676559448242},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29494011402130127},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2886863946914673},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.2615565061569214},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.13573119044303894},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08026584982872009}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:lup.lub.lu.se:866d4503-4437-47ac-9e16-b597ca78427e","is_oa":false,"landing_page_url":"https://lup.lub.lu.se/record/866d4503-4437-47ac-9e16-b597ca78427e","pdf_url":null,"source":{"id":"https://openalex.org/S4306400536","display_name":"Lund University Publications (Lund University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I187531555","host_organization_name":"Lund University","host_organization_lineage":["https://openalex.org/I187531555"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1636081627","https://openalex.org/W1986593582","https://openalex.org/W2025311305","https://openalex.org/W2025371899","https://openalex.org/W2047314945","https://openalex.org/W2055264244","https://openalex.org/W2074501647","https://openalex.org/W2093517126","https://openalex.org/W2106822551","https://openalex.org/W2107300011","https://openalex.org/W2113762408","https://openalex.org/W2116031726","https://openalex.org/W2123346926","https://openalex.org/W2123492259","https://openalex.org/W2144992143","https://openalex.org/W2155722796","https://openalex.org/W2170248460","https://openalex.org/W2178225550","https://openalex.org/W2240661524","https://openalex.org/W2412423954","https://openalex.org/W4231726431"],"related_works":["https://openalex.org/W1972230816","https://openalex.org/W2337188777","https://openalex.org/W1966389522","https://openalex.org/W2104261629","https://openalex.org/W4320024888","https://openalex.org/W4313130483","https://openalex.org/W2074287313","https://openalex.org/W4205356102","https://openalex.org/W2492381230","https://openalex.org/W2220576269"],"abstract_inverted_index":{"The":[0],"traditional":[1],"parametric":[2],"approach":[3,90],"to":[4,18,91],"Granger":[5],"causality":[6],"(GC),":[7],"based":[8],"on":[9],"linear":[10],"vector":[11],"autoregressive":[12],"modeling,":[13],"suffers":[14],"from":[15],"difficulties":[16],"related":[17],"the":[19,23,37,53,58,69,88,92],"inaccurate":[20],"modeling":[21],"of":[22,40,57,94],"generative":[24],"process.":[25],"These":[26],"limits":[27],"can":[28],"be":[29],"solved":[30],"by":[31,80],"using":[32,62],"nonparametric":[33],"spectral":[34,45,60,65,77],"estimates":[35],"in":[36,98],"frequency-domain":[38],"formulation":[39],"GC,":[41],"also":[42],"known":[43],"as":[44],"GC.":[46],"In":[47],"a":[48],"simulation":[49],"study,":[50],"we":[51,86],"compare":[52],"mean":[54],"square":[55],"error":[56],"estimated":[59],"GC":[61,78],"different":[63],"multitaper":[64],"estimators,":[66],"finding":[67],"that":[68],"Peak":[70],"Matched":[71],"multitapers":[72],"are":[73],"preferable":[74],"for":[75],"estimating":[76],"characterized":[79],"peaks.":[81],"As":[82],"an":[83],"illustrative":[84],"example,":[85],"apply":[87],"non-parametric":[89],"analysis":[93],"brain":[95],"functional":[96],"connectivity":[97],"steady-state":[99],"visually":[100],"evoked":[101],"potentials.":[102]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
