{"id":"https://openalex.org/W1865022507","doi":"https://doi.org/10.1109/iscas.2002.1010294","title":"Nonlinear prediction of brain electrical activity in epilepsy with a Volterra RLS algorithm","display_name":"Nonlinear prediction of brain electrical activity in epilepsy with a Volterra RLS algorithm","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W1865022507","doi":"https://doi.org/10.1109/iscas.2002.1010294","mag":"1865022507"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2002.1010294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2002.1010294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353)","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/A5053432318","display_name":"C. Niederh\u00f6fer","orcid":null},"institutions":[{"id":"https://openalex.org/I114090438","display_name":"Goethe University Frankfurt","ror":"https://ror.org/04cvxnb49","country_code":"DE","type":"education","lineage":["https://openalex.org/I114090438"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"C. Niederhofer","raw_affiliation_strings":["Institute of Applied Physics, University of Frankfurt, Frankfurt, A.M., Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Applied Physics, University of Frankfurt, Frankfurt, A.M., Germany","institution_ids":["https://openalex.org/I114090438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069631511","display_name":"Shaolong Suna","orcid":null},"institutions":[{"id":"https://openalex.org/I114090438","display_name":"Goethe University Frankfurt","ror":"https://ror.org/04cvxnb49","country_code":"DE","type":"education","lineage":["https://openalex.org/I114090438"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"S. Suna","raw_affiliation_strings":["Institute of Applied Physics, University of Frankfurt, Frankfurt, A.M., Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Applied Physics, University of Frankfurt, Frankfurt, A.M., Germany","institution_ids":["https://openalex.org/I114090438"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012451668","display_name":"Ronald Tetzlaff","orcid":"https://orcid.org/0000-0001-7436-0103"},"institutions":[{"id":"https://openalex.org/I114090438","display_name":"Goethe University Frankfurt","ror":"https://ror.org/04cvxnb49","country_code":"DE","type":"education","lineage":["https://openalex.org/I114090438"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"R. Tetzlaff","raw_affiliation_strings":["Institute of Applied Physics, University of Frankfurt, Frankfurt, A.M., Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Applied Physics, University of Frankfurt, Frankfurt, A.M., Germany","institution_ids":["https://openalex.org/I114090438"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114090438"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"III","last_page":"595"},"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/T11236","display_name":"Control Systems and Identification","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/epilepsy","display_name":"Epilepsy","score":0.7072309255599976},{"id":"https://openalex.org/keywords/recursive-least-squares-filter","display_name":"Recursive least squares filter","score":0.60568767786026},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6028897762298584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5257638096809387},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5010359287261963},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4878520965576172},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4666317403316498},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.14155662059783936},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13870298862457275},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1291624903678894},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07379364967346191}],"concepts":[{"id":"https://openalex.org/C2778186239","wikidata":"https://www.wikidata.org/wiki/Q41571","display_name":"Epilepsy","level":2,"score":0.7072309255599976},{"id":"https://openalex.org/C145249878","wikidata":"https://www.wikidata.org/wiki/Q2835868","display_name":"Recursive least squares filter","level":3,"score":0.60568767786026},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6028897762298584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5257638096809387},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5010359287261963},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4878520965576172},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4666317403316498},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.14155662059783936},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13870298862457275},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1291624903678894},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07379364967346191},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"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/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas.2002.1010294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2002.1010294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W1991777572","https://openalex.org/W2134827135"],"related_works":["https://openalex.org/W2395385109","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2773633178","https://openalex.org/W2802335767","https://openalex.org/W2080101436","https://openalex.org/W4388090985","https://openalex.org/W2356350882","https://openalex.org/W1545074592","https://openalex.org/W1588384605"],"abstract_inverted_index":{"Approximately":[0],"0.3%":[1],"of":[2,18,33,47,69,72],"the":[3,15,19,31,73],"world's":[4],"population":[5],"is":[6],"suffering":[7],"from":[8],"a":[9,67],"focal":[10],"epilepsy.":[11],"In":[12],"this":[13],"paper":[14],"bioelectrical":[16],"activity":[17],"human":[20],"brain":[21],"in":[22,58],"epilepsy":[23],"will":[24,36,61,76],"be":[25,37,62,77],"analyzed":[26],"with":[27],"Volterra-systems":[28],"(VS),":[29],"whereas":[30],"kernels":[32],"different":[34],"orders":[35],"determined":[38],"by":[39],"using":[40],"an":[41],"RLS":[42],"(recursive":[43],"least":[44],"squares)":[45],"method":[46],"reduced":[48],"computation":[49],"complexity.":[50],"The":[51],"prediction":[52,74],"gain":[53],"for":[54,66],"data":[55],"segments":[56],"obtained":[57],"presurgical":[59],"evaluations":[60],"given":[63],"and":[64],"criteria":[65],"detection":[68],"distinct":[70],"changes":[71],"coefficients":[75],"proposed.":[78]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}