{"id":"https://openalex.org/W4390481271","doi":"https://doi.org/10.1109/iccma59762.2023.10374691","title":"Which Methods Perform Better for Real-Time Hurst Parameter Estimation?","display_name":"Which Methods Perform Better for Real-Time Hurst Parameter Estimation?","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4390481271","doi":"https://doi.org/10.1109/iccma59762.2023.10374691"},"language":"en","primary_location":{"id":"doi:10.1109/iccma59762.2023.10374691","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccma59762.2023.10374691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International Conference on Control, Mechatronics and Automation (ICCMA)","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/A5100696404","display_name":"Daniel Chen","orcid":"https://orcid.org/0000-0002-4716-549X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daniel Chen","raw_affiliation_strings":["University of California,Management, Entrepreneurship, & Technology (M.E.T.), Electrical Engineering and Computer Science and Business Administration,Berkeley Berkeley,CA,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Management, Entrepreneurship, & Technology (M.E.T.), Electrical Engineering and Computer Science and Business Administration,Berkeley Berkeley,CA,United States","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100696404"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":4.6246,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.94591985,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9782999753952026,"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/hurst-exponent","display_name":"Hurst exponent","score":0.8996442556381226},{"id":"https://openalex.org/keywords/detrended-fluctuation-analysis","display_name":"Detrended fluctuation analysis","score":0.8519256114959717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6886674165725708},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6060153841972351},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5688057541847229},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.49412253499031067},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4395114779472351},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4265478551387787},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3356836140155792},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27323755621910095},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19975244998931885},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1973658800125122}],"concepts":[{"id":"https://openalex.org/C96835011","wikidata":"https://www.wikidata.org/wiki/Q1638718","display_name":"Hurst exponent","level":2,"score":0.8996442556381226},{"id":"https://openalex.org/C21689155","wikidata":"https://www.wikidata.org/wiki/Q2451452","display_name":"Detrended fluctuation analysis","level":3,"score":0.8519256114959717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6886674165725708},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6060153841972351},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5688057541847229},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.49412253499031067},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4395114779472351},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4265478551387787},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3356836140155792},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27323755621910095},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19975244998931885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1973658800125122},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccma59762.2023.10374691","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccma59762.2023.10374691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International Conference on Control, Mechatronics and Automation (ICCMA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W66305751","https://openalex.org/W1969611538","https://openalex.org/W2112463371","https://openalex.org/W2117343462","https://openalex.org/W2478961926","https://openalex.org/W2566459171","https://openalex.org/W2917944382","https://openalex.org/W3046985897","https://openalex.org/W6646587983"],"related_works":["https://openalex.org/W4321505114","https://openalex.org/W2401810189","https://openalex.org/W2057384585","https://openalex.org/W2035064929","https://openalex.org/W2073997720","https://openalex.org/W2795419853","https://openalex.org/W2911012399","https://openalex.org/W2125635163","https://openalex.org/W2997775184","https://openalex.org/W2058567967"],"abstract_inverted_index":{"Long-range":[0],"dependence":[1],"(LRD)":[2],"in":[3,13,51,57,95,112],"complex":[4,25,59,64],"time":[5,60,97,115],"series":[6,61],"is":[7,43,66,89],"becoming":[8],"an":[9],"increasingly":[10],"important":[11],"aspect":[12],"the":[14,24,39,49,54,93,96,108,113,127],"era":[15],"of":[16,53,143,155],"big":[17],"data":[18],"as":[19],"we":[20],"explore":[21],"further":[22,152],"into":[23],"world.":[26],"From":[27],"natural":[28],"processes":[29],"like":[30,38],"heart":[31],"rate":[32],"variability":[33],"(HRV)":[34],"or":[35,78],"manmade":[36],"systems":[37,65],"stock":[40],"market,":[41],"LRD":[42,50,94,114],"omnipresent.":[44],"As":[45],"such,":[46],"accurately":[47],"characterizing":[48],"terms":[52],"Hurst":[55,72,109,144,158],"parameter":[56,73,110,159],"these":[58],"generated":[62],"from":[63],"important.":[67],"Most":[68],"existing":[69],"methods":[70],"for":[71,76,139,151],"estimation":[74,142],"are":[75,149],"batch":[77],"offline":[79],"processing.":[80],"To":[81],"achieve":[82],"real-time":[83,141,157],"evaluation,":[84],"a":[85],"moving":[86],"window":[87],"approach":[88],"applied":[90],"when":[91],"quantifying":[92],"series.":[98,116],"This":[99],"paper":[100],"focuses":[101],"on":[102],"evaluating":[103],"various":[104],"techniques":[105,118],"that":[106],"estimate":[107],"embedded":[111],"Nine":[117],"were":[119,123],"analyzed,":[120],"and":[121,135],"three":[122],"determined":[124],"to":[125],"be":[126],"most":[128],"accurate:":[129],"Higuchi's":[130],"method,":[131],"Diffusion":[132],"Entropy":[133],"Analysis,":[134],"Detrended":[136],"Fluctuation":[137],"Analysis":[138],"online":[140,156],"parameters.":[145],"All":[146],"reported":[147],"results":[148],"reproducible":[150],"robustness":[153],"evaluation":[154],"estimation.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}