{"id":"https://openalex.org/W2913729147","doi":"https://doi.org/10.1109/icassp.2019.8682601","title":"Dynamical Component Analysis (DYCA) and Its Application on Epileptic EEG","display_name":"Dynamical Component Analysis (DYCA) and Its Application on Epileptic EEG","publication_year":2019,"publication_date":"2019-04-16","ids":{"openalex":"https://openalex.org/W2913729147","doi":"https://doi.org/10.1109/icassp.2019.8682601","mag":"2913729147"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682601","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682601","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1902.01777","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000024102","display_name":"Katharina Korn","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102060","display_name":"Ansbach University of Applied Sciences","ror":"https://ror.org/0167rnj42","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210102060"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Katharina Korn","raw_affiliation_strings":["Faculty of Engineering Sciences, Ansbach University of Applied Sciences, Ansbach, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Sciences, Ansbach University of Applied Sciences, Ansbach, Germany","institution_ids":["https://openalex.org/I4210102060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068391167","display_name":"Bastian Seifert","orcid":"https://orcid.org/0000-0002-2207-8285"},"institutions":[{"id":"https://openalex.org/I4210102060","display_name":"Ansbach University of Applied Sciences","ror":"https://ror.org/0167rnj42","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210102060"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bastian Seifert","raw_affiliation_strings":["Faculty of Engineering Sciences, Ansbach University of Applied Sciences, Ansbach, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Sciences, Ansbach University of Applied Sciences, Ansbach, Germany","institution_ids":["https://openalex.org/I4210102060"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027967416","display_name":"Christian Uhl","orcid":"https://orcid.org/0000-0003-0596-7221"},"institutions":[{"id":"https://openalex.org/I4210102060","display_name":"Ansbach University of Applied Sciences","ror":"https://ror.org/0167rnj42","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210102060"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Uhl","raw_affiliation_strings":["Faculty of Engineering Sciences, Ansbach University of Applied Sciences, Ansbach, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering Sciences, Ansbach University of Applied Sciences, Ansbach, Germany","institution_ids":["https://openalex.org/I4210102060"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210102060"],"apc_list":null,"apc_paid":null,"fwci":1.0019,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.75354556,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1100","last_page":"1104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9993000030517578,"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/T12946","display_name":"Fractal and DNA sequence analysis","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.7647154331207275},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6353130340576172},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.5931522846221924},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5833565592765808},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5691771507263184},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5664464831352234},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5484755635261536},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5061401724815369},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48420265316963196},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.48086339235305786},{"id":"https://openalex.org/keywords/component-analysis","display_name":"Component analysis","score":0.47697505354881287},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.46298351883888245},{"id":"https://openalex.org/keywords/eigendecomposition-of-a-matrix","display_name":"Eigendecomposition of a matrix","score":0.4517192840576172},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4441056251525879},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37844541668891907},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.17584466934204102},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07511606812477112}],"concepts":[{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.7647154331207275},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6353130340576172},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.5931522846221924},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5833565592765808},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5691771507263184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5664464831352234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5484755635261536},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5061401724815369},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48420265316963196},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.48086339235305786},{"id":"https://openalex.org/C2780692498","wikidata":"https://www.wikidata.org/wiki/Q16950721","display_name":"Component analysis","level":2,"score":0.47697505354881287},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.46298351883888245},{"id":"https://openalex.org/C169756996","wikidata":"https://www.wikidata.org/wiki/Q194919","display_name":"Eigendecomposition of a matrix","level":3,"score":0.4517192840576172},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4441056251525879},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37844541668891907},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.17584466934204102},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07511606812477112},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"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/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2019.8682601","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682601","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1902.01777","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.01777","pdf_url":"https://arxiv.org/pdf/1902.01777","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":{"id":"pmh:oai:arXiv.org:1902.01777","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.01777","pdf_url":"https://arxiv.org/pdf/1902.01777","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2003409024","https://openalex.org/W2024633000","https://openalex.org/W2057779744","https://openalex.org/W2123649031","https://openalex.org/W2294798173","https://openalex.org/W2334971550","https://openalex.org/W2627799415","https://openalex.org/W2759483166","https://openalex.org/W2952497813","https://openalex.org/W3102820815","https://openalex.org/W3104616224"],"related_works":["https://openalex.org/W1971575144","https://openalex.org/W2369494890","https://openalex.org/W2073510591","https://openalex.org/W1888749522","https://openalex.org/W2139404519","https://openalex.org/W3027745756","https://openalex.org/W1513845058","https://openalex.org/W2121025724","https://openalex.org/W2393502243","https://openalex.org/W2123927273"],"abstract_inverted_index":{"Dynamical":[0],"Component":[1],"Analysis":[2],"(DyCA)":[3],"is":[4,21,38],"a":[5,27],"recently-proposed":[6],"method":[7],"to":[8,12,35,42,53,95],"detect":[9],"projection":[10],"vectors":[11],"reduce":[13],"the":[14,24,55,58,80],"dimensionality":[15],"of":[16,26,45,72,85],"multi-variate":[17],"deterministic":[18],"datasets.":[19],"It":[20],"based":[22],"on":[23],"solution":[25],"generalized":[28],"eigenvalue":[29],"problem":[30],"and":[31,40,57,68,79,90],"therefore":[32],"straight":[33],"forward":[34],"implement.":[36],"DyCA":[37,73],"presented":[39],"applied":[41],"EEG":[43],"data":[44],"epileptic":[46],"seizures.":[47],"The":[48,70],"obtained":[49,81],"eigenvectors":[50],"are":[51,64,74,93],"used":[52],"project":[54],"signal":[56],"corresponding":[59],"trajectories":[60],"in":[61,83],"phase":[62],"space":[63],"compared":[65,94],"with":[66],"PCA":[67],"ICA-projections.":[69],"eigenvalues":[71],"utilized":[75],"for":[76],"seizure":[77,97],"detection":[78,98],"results":[82],"terms":[84],"specificity,":[86],"false":[87],"discovery":[88],"rate":[89,92],"miss":[91],"other":[96],"algorithms.":[99]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
