{"id":"https://openalex.org/W1582661268","doi":"https://doi.org/10.1109/ijcnn.2005.1556288","title":"Comparison of TDNN training algorithms in brain machine interfaces","display_name":"Comparison of TDNN training algorithms in brain machine interfaces","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W1582661268","doi":"https://doi.org/10.1109/ijcnn.2005.1556288","mag":"1582661268"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1556288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1556288","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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/A5100383445","display_name":"Yiwen Wang","orcid":"https://orcid.org/0000-0002-1878-6182"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiwen Wang","raw_affiliation_strings":["Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA","Comput. NeuroEng. Lab., Florida Univ., Gainesville, FL, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Comput. NeuroEng. Lab., Florida Univ., Gainesville, FL, USA#TAB#","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111463337","display_name":"Sung-Phil Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sung-Phil Kim","raw_affiliation_strings":["Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA","Comput. NeuroEng. Lab., Florida Univ., Gainesville, FL, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Comput. NeuroEng. Lab., Florida Univ., Gainesville, FL, USA#TAB#","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019504861","display_name":"Jos\u00e9 C. Pr\u0131\u0301ncipe","orcid":"https://orcid.org/0000-0002-3449-3531"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J.C. Principe","raw_affiliation_strings":["Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA","Comput. NeuroEng. Lab., Florida Univ., Gainesville, FL, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Comput. NeuroEng. Lab., Florida Univ., Gainesville, FL, USA#TAB#","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100383445"],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":1.603,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.80851064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"4","issue":null,"first_page":"2459","last_page":"2462"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10581","display_name":"Neural dynamics and brain function","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7711046934127808},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7554134726524353},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.7473137378692627},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6749562621116638},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.6177268028259277},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.6013818979263306},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5283665657043457},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.52195805311203},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.517414927482605},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46907490491867065},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3406059741973877}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7711046934127808},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7554134726524353},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.7473137378692627},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6749562621116638},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.6177268028259277},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.6013818979263306},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5283665657043457},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.52195805311203},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.517414927482605},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46907490491867065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3406059741973877},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn.2005.1556288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1556288","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.641.1480","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.641.1480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cnel.ufl.edu/files/1177192664.pdf","raw_type":"text"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-82741","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-82741","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"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":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1483156930","https://openalex.org/W1543237449","https://openalex.org/W1900101064","https://openalex.org/W1943730788","https://openalex.org/W2002096058","https://openalex.org/W2023295798","https://openalex.org/W2041248708","https://openalex.org/W2051812123","https://openalex.org/W2072151998","https://openalex.org/W2095504054","https://openalex.org/W2112790465","https://openalex.org/W2127260043","https://openalex.org/W2131854908","https://openalex.org/W6679496737"],"related_works":["https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W1966421350","https://openalex.org/W4312154385","https://openalex.org/W2185955524","https://openalex.org/W2104893957","https://openalex.org/W2782354941","https://openalex.org/W2050937272","https://openalex.org/W1889674915"],"abstract_inverted_index":{"Linear":[0,25],"or":[1],"non-linear":[2],"models":[3,26],"are":[4],"used":[5],"in":[6,64],"brain":[7],"machine":[8],"interfaces":[9],"(BIMIs)":[10],"to":[11,16,84,101],"map":[12],"the":[13,17,21,41,86,103],"neural":[14,32,48],"activity":[15,33],"associated":[18],"behavior,":[19],"typically":[20],"primate's":[22],"hand":[23,35],"position.":[24],"assume":[27],"a":[28,54,65],"linear":[29,58,95],"relationship":[30],"between":[31],"and":[34,71,107],"position":[36],"that":[37,51],"may":[38],"not":[39],"be":[40,46],"case.":[42],"A":[43],"solution":[44],"would":[45],"time-delay":[47],"network":[49],"(TDNN)":[50],"provides":[52],"effectively":[53],"nonlinear":[55],"combination":[56],"of":[57,68],"models.":[59],"However,":[60],"this":[61],"model":[62],"results":[63],"drastic":[66],"increase":[67],"free":[69,104],"parameters":[70,105],"slow":[72],"convergence":[73],"when":[74],"trained":[75],"by":[76,88],"an":[77],"error":[78],"backpropagation":[79],"learning":[80],"rule.":[81],"We":[82],"propose":[83],"train":[85],"TDNN":[87],"scaled":[89],"conjugate":[90],"gradient,":[91],"which":[92],"avoids":[93],"time-consuming":[94],"search,":[96],"coupled":[97],"with":[98],"weight":[99],"decay":[100],"reduce":[102],"number":[106],"produce":[108],"generally":[109],"faster":[110],"convergence.":[111]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}