{"id":"https://openalex.org/W2166742826","doi":"https://doi.org/10.1109/ijcnn.2011.6033304","title":"Hidden Markov model estimation based on alpha-EM algorithm: Discrete and continuous alpha-HMMs","display_name":"Hidden Markov model estimation based on alpha-EM algorithm: Discrete and continuous alpha-HMMs","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2166742826","doi":"https://doi.org/10.1109/ijcnn.2011.6033304","mag":"2166742826"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2011.6033304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2011.6033304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2011 International Joint Conference on Neural Networks","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/A5004156746","display_name":"Yasuo Matsuyama","orcid":"https://orcid.org/0000-0002-0819-9240"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yasuo Matsuyama","raw_affiliation_strings":["Department of Computer Science and Engineering, Waseda University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004156746"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":2.1378,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.89377509,"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":"808","last_page":"816"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9846000075340271,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9843999743461609,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.8126102685928345},{"id":"https://openalex.org/keywords/alpha","display_name":"Alpha (finance)","score":0.6723846197128296},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6626359224319458},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.619619607925415},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5918957591056824},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5270633697509766},{"id":"https://openalex.org/keywords/forward-algorithm","display_name":"Forward algorithm","score":0.5247088670730591},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.46770378947257996},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.42202329635620117},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3851420283317566},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.3006042242050171},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2823260426521301},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.2154163122177124},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14806681871414185},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1455157995223999},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.06811639666557312}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8126102685928345},{"id":"https://openalex.org/C64943373","wikidata":"https://www.wikidata.org/wiki/Q2651003","display_name":"Alpha (finance)","level":4,"score":0.6723846197128296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6626359224319458},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.619619607925415},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5918957591056824},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5270633697509766},{"id":"https://openalex.org/C196455857","wikidata":"https://www.wikidata.org/wiki/Q5473264","display_name":"Forward algorithm","level":5,"score":0.5247088670730591},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.46770378947257996},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.42202329635620117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3851420283317566},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.3006042242050171},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2823260426521301},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.2154163122177124},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14806681871414185},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1455157995223999},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.06811639666557312},{"id":"https://openalex.org/C49453240","wikidata":"https://www.wikidata.org/wiki/Q1592163","display_name":"Construct validity","level":3,"score":0.0},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2011.6033304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2011.6033304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2011 International Joint Conference on Neural Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322638","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1512429158","https://openalex.org/W1560013842","https://openalex.org/W1594432185","https://openalex.org/W1980800561","https://openalex.org/W2003333103","https://openalex.org/W2009570821","https://openalex.org/W2014089984","https://openalex.org/W2049633694","https://openalex.org/W2086699924","https://openalex.org/W2109693535","https://openalex.org/W2115233539","https://openalex.org/W2125838338","https://openalex.org/W2159139259","https://openalex.org/W2595142274","https://openalex.org/W3148186152","https://openalex.org/W4245668478","https://openalex.org/W6630838124"],"related_works":["https://openalex.org/W2161328464","https://openalex.org/W1978153144","https://openalex.org/W102848802","https://openalex.org/W2382132287","https://openalex.org/W2982058819","https://openalex.org/W1510894296","https://openalex.org/W2130734797","https://openalex.org/W2172249169","https://openalex.org/W3176361882","https://openalex.org/W2150616621"],"abstract_inverted_index":{"Fast":[0],"estimation":[1],"algorithms":[2,14],"for":[3,8,135],"Hidden":[4],"Markov":[5],"models":[6],"(HMMs)":[7],"given":[9],"data":[10,158],"are":[11,34,83,116,119,126,159],"presented.":[12],"These":[13],"start":[15],"from":[16],"the":[17,22,35,38,45,64,88,103,110,141,144,147],"alpha-EM":[18,145],"algorithm":[19],"which":[20,82],"includes":[21],"traditional":[23,32],"log-EM":[24],"as":[25,97],"its":[26,114],"proper":[27],"subset.":[28],"Since":[29,102],"existing":[30],"or":[31],"HMMs":[33],"outcome":[36],"of":[37,63,99,113,122,143],"log-EM,":[39],"it":[40,52],"had":[41],"been":[42],"expected":[43],"that":[44,55,98],"alpha-HMM":[46],"would":[47],"exist.":[48],"In":[49,72],"this":[50,56],"paper,":[51],"is":[53,58,106,150],"shown":[54],"foresight":[57],"true":[59],"by":[60],"using":[61],"methods":[62],"iteration":[65,93],"index":[66],"shift":[67],"and":[68,85,130,133,137],"likelihood":[69],"ratio":[70],"expansion.":[71],"each":[73],"iteration,":[74],"new":[75,104],"update":[76],"equations":[77],"utilize":[78],"one-step":[79],"past":[80],"terms":[81],"computed":[84],"stored":[86],"during":[87],"previous":[89],"maximization":[90],"step.":[91],"Therefore,":[92],"speedup":[94,148],"directly":[95],"appears":[96],"CPU":[100],"time.":[101],"method":[105],"theoretically":[107,151],"based":[108],"on":[109],"alpha-EM,":[111],"all":[112],"properties":[115,142],"inherited.":[117],"There":[118],"eight":[120],"types":[121],"alpha-HMMs":[123],"derived.":[124],"They":[125],"discrete,":[127],"continuous,":[128],"semi-continuous":[129],"discrete-continuous":[131],"alpha-HMMs,":[132],"both":[134],"single":[136],"multiple":[138],"sequences.":[139],"Using":[140],"algorithm,":[146],"property":[149],"analyzed.":[152],"Experimental":[153],"results":[154],"including":[155],"real":[156],"world":[157],"given.":[160]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}