{"id":"https://openalex.org/W1968367328","doi":"https://doi.org/10.1142/s0218127400000074","title":"NONLINEAR PREDICTION AND COMPLEXITY OF ALPHA EEG ACTIVITY","display_name":"NONLINEAR PREDICTION AND COMPLEXITY OF ALPHA EEG ACTIVITY","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W1968367328","doi":"https://doi.org/10.1142/s0218127400000074","mag":"1968367328"},"language":"en","primary_location":{"id":"doi:10.1142/s0218127400000074","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218127400000074","pdf_url":null,"source":{"id":"https://openalex.org/S81011612","display_name":"International Journal of Bifurcation and Chaos","issn_l":"0218-1274","issn":["0218-1274","1793-6551"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Bifurcation and Chaos","raw_type":"journal-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/A5111884160","display_name":"Michael E. Brandt","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"MICHAEL E. BRANDT","raw_affiliation_strings":["Neurosignal Analysis Laboratory, University of Texas Medical School, Houston, Texas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neurosignal Analysis Laboratory, University of Texas Medical School, Houston, Texas, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078800492","display_name":"Ahmet Ademo\u011flu","orcid":"https://orcid.org/0000-0003-1230-9518"},"institutions":[{"id":"https://openalex.org/I4405392","display_name":"Bo\u011fazi\u00e7i University","ror":"https://ror.org/03z9tma90","country_code":"TR","type":"education","lineage":["https://openalex.org/I4405392"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"AHMET ADEMO\u011eLU","raw_affiliation_strings":["Biomedical Engineering Institute,  Bo\u011fazi\u00e7i University, Istanbul, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Biomedical Engineering Institute,  Bo\u011fazi\u00e7i University, Istanbul, Turkey","institution_ids":["https://openalex.org/I4405392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088056956","display_name":"Walter S. Pritchard","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159832","display_name":"Reynolds American (United States)","ror":"https://ror.org/05qcjd272","country_code":"US","type":"company","lineage":["https://openalex.org/I4210159832"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"WALTER S. PRITCHARD","raw_affiliation_strings":["Psychophysiology Laboratory, R.J. Reynolds Tobacco Company, Winston-Salem, North Carolina, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Psychophysiology Laboratory, R.J. Reynolds Tobacco Company, Winston-Salem, North Carolina, USA","institution_ids":["https://openalex.org/I4210159832"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111884160"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":0.1669,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.48041326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"01","first_page":"123","last_page":"133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9970999956130981,"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":0.9970999956130981,"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/T10244","display_name":"Chaos control and synchronization","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"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":0.9962000250816345,"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/autoregressive-model","display_name":"Autoregressive model","score":0.7308821082115173},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.7197348475456238},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6559810638427734},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5715916752815247},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5441717505455017},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5403298735618591},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5087977051734924},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4899989664554596},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.4659123718738556},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.44091707468032837},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4342103600502014},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4273204207420349},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4112759828567505},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37331318855285645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3309676945209503},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3308853507041931},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23472169041633606},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08976376056671143}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7308821082115173},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.7197348475456238},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6559810638427734},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5715916752815247},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5441717505455017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5403298735618591},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5087977051734924},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4899989664554596},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4659123718738556},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.44091707468032837},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4342103600502014},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4273204207420349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4112759828567505},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37331318855285645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3309676945209503},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3308853507041931},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23472169041633606},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08976376056671143},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218127400000074","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218127400000074","pdf_url":null,"source":{"id":"https://openalex.org/S81011612","display_name":"International Journal of Bifurcation and Chaos","issn_l":"0218-1274","issn":["0218-1274","1793-6551"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Bifurcation and Chaos","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1662665","https://openalex.org/W1498759836","https://openalex.org/W1518194904","https://openalex.org/W1549386224","https://openalex.org/W1967774897","https://openalex.org/W1979819271","https://openalex.org/W1996511030","https://openalex.org/W1998367480","https://openalex.org/W2005277457","https://openalex.org/W2011974292","https://openalex.org/W2019221237","https://openalex.org/W2022044299","https://openalex.org/W2024604923","https://openalex.org/W2027208707","https://openalex.org/W2029401646","https://openalex.org/W2030032088","https://openalex.org/W2038488793","https://openalex.org/W2039657881","https://openalex.org/W2046328835","https://openalex.org/W2049865363","https://openalex.org/W2060568420","https://openalex.org/W2065991392","https://openalex.org/W2066366061","https://openalex.org/W2074496265","https://openalex.org/W2088665078","https://openalex.org/W2097580026","https://openalex.org/W2098746383","https://openalex.org/W2109132687","https://openalex.org/W2117178635","https://openalex.org/W2121594221","https://openalex.org/W2402041901","https://openalex.org/W2591949766","https://openalex.org/W2788426243","https://openalex.org/W2799514739","https://openalex.org/W3015317271","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2171218219","https://openalex.org/W2150410159","https://openalex.org/W1972271943","https://openalex.org/W3150905897","https://openalex.org/W4327525404","https://openalex.org/W4287185323","https://openalex.org/W1520183331","https://openalex.org/W2099889858","https://openalex.org/W2349019353","https://openalex.org/W2154965898"],"abstract_inverted_index":{"Two":[0],"prediction":[1,95,110,198],"techniques":[2,111],"were":[3,112],"used":[4],"to":[5,38,114,165,176],"investigate":[6],"the":[7,11,18,58,177,188],"dynamical":[8],"complexity":[9],"of":[10,57],"alpha":[12],"EEG;":[13],"a":[14,42,88,142,202],"nonlinear":[15,204],"method":[16],"using":[17,53,96],"K-nearest-neighbor":[19],"local":[20],"linear":[21,29,82],"(KNNLL)":[22],"approximation,":[23],"and":[24,63,131],"one":[25],"based":[26],"on":[27],"global":[28],"autoregressive":[30],"(AR)":[31],"modeling.":[32],"Generally,":[33],"KNNLL":[34,74,97,138],"has":[35],"more":[36,154],"ability":[37],"predict":[39],"nonlinearity":[40],"in":[41,185,210],"chaotic":[43,166],"time":[44,84,167],"series":[45,168],"under":[46,129],"moderately":[47],"noisy":[48,55,160,203],"conditions":[49],"as":[50,87,163],"demonstrated":[51],"by":[52,201],"increasingly":[54],"realizations":[56],"H\u00e9non":[59],"(a":[60,65],"low-dimensional":[61],"chaotic)":[62,67],"Mackey\u2013Glass":[64],"high-dimensional":[66],"maps.":[68],"However,":[69,187],"at":[70,104],"higher":[71],"noise":[72],"levels":[73],"performs":[75],"no":[76,99],"better":[77,100],"than":[78,101,149],"AR":[79,102,150],"prediction.":[80,151],"For":[81],"stochastic":[83],"series,":[85],"such":[86],"sine":[89,161],"wave":[90],"with":[91,169,196],"added":[92,170],"Gaussian":[93],"noise,":[94],"is":[98],"even":[103],"very":[105],"low":[106],"signal-to-noise":[107],"ratios.":[108],"Both":[109],"applied":[113],"resting":[115],"EEGs":[116],"(O2":[117],"scalp":[118],"recording":[119],"site,":[120],"10\u201320":[121],"EEG":[122,181,192],"system)":[123],"from":[124],"ten":[125],"normal":[126],"adult":[127],"subjects":[128],"eyes-closed":[130],"eyes-open":[132],"conditions.":[133],"In":[134],"all":[135],"recordings":[136],"tested,":[137],"did":[139],"not":[140],"yield":[141],"lower":[143],"root":[144],"mean":[145],"squared":[146],"error":[147],"(RMSE)":[148],"This":[152,172],"result":[153],"closely":[155],"resembles":[156],"that":[157,179,190],"obtained":[158],"for":[159],"waves":[162],"opposed":[164],"noise.":[171],"lends":[173],"further":[174],"support":[175],"notion":[178],"these":[180],"signals":[182],"are":[183],"linear-stochastic":[184],"nature.":[186],"possibility":[189],"some":[191],"signals,":[193],"particularly":[194],"those":[195],"high":[197],"errors":[199],"produced":[200],"system":[205],"cannot":[206],"be":[207],"ruled":[208],"out":[209],"this":[211],"study.":[212]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}