{"id":"https://openalex.org/W3145356632","doi":"https://doi.org/10.1155/2021/5577486","title":"Using Machine Learning Algorithm to Describe the Connection between the Types and Characteristics of Music Signal","display_name":"Using Machine Learning Algorithm to Describe the Connection between the Types and Characteristics of Music Signal","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3145356632","doi":"https://doi.org/10.1155/2021/5577486","mag":"3145356632"},"language":"en","primary_location":{"id":"doi:10.1155/2021/5577486","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/5577486","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/5577486.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2021/5577486.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101460115","display_name":"Bo Sun","orcid":"https://orcid.org/0000-0002-7903-5841"},"institutions":[{"id":"https://openalex.org/I125687163","display_name":"City College of New York","ror":"https://ror.org/00wmhkr98","country_code":"US","type":"education","lineage":["https://openalex.org/I125687163"]},{"id":"https://openalex.org/I39521962","display_name":"Hunan City University","ror":"https://ror.org/01vd7vb53","country_code":"CN","type":"education","lineage":["https://openalex.org/I39521962"]},{"id":"https://openalex.org/I4210093530","display_name":"City College","ror":"https://ror.org/00h90tg62","country_code":"US","type":"education","lineage":["https://openalex.org/I4210093530"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Bo Sun","raw_affiliation_strings":["School of Arts, Hunan City College, Yiyang, Hunan 413000, China","School of Arts, Hunan City College, Yiyang, Hunan 413000"],"raw_orcid":"https://orcid.org/0000-0002-7903-5841","affiliations":[{"raw_affiliation_string":"School of Arts, Hunan City College, Yiyang, Hunan 413000, China","institution_ids":["https://openalex.org/I39521962"]},{"raw_affiliation_string":"School of Arts, Hunan City College, Yiyang, Hunan 413000","institution_ids":["https://openalex.org/I125687163","https://openalex.org/I39521962","https://openalex.org/I4210093530"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101460115"],"corresponding_institution_ids":["https://openalex.org/I125687163","https://openalex.org/I39521962","https://openalex.org/I4210093530"],"apc_list":{"value":2300,"currency":"USD","value_usd":2550},"apc_paid":{"value":2300,"currency":"USD","value_usd":2550},"fwci":0.4177,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58490156,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9886000156402588,"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/T11309","display_name":"Music and Audio Processing","score":0.9886000156402588,"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/computer-science","display_name":"Computer science","score":0.6904614567756653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6742928624153137},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6403613686561584},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6037180423736572},{"id":"https://openalex.org/keywords/multiple-signal-classification","display_name":"Multiple signal classification","score":0.5683978199958801},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5648065209388733},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.45160236954689026},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41200146079063416},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37819936871528625},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3248274624347687}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6904614567756653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6742928624153137},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6403613686561584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6037180423736572},{"id":"https://openalex.org/C206118826","wikidata":"https://www.wikidata.org/wiki/Q3841682","display_name":"Multiple signal classification","level":3,"score":0.5683978199958801},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5648065209388733},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.45160236954689026},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41200146079063416},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37819936871528625},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3248274624347687},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2021/5577486","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/5577486","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/5577486.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:5577486","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/complexity/2021/5577486.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"},{"id":"pmh:oai:doaj.org/article:af13b75d5b8142f7922bd86eaa20f444","is_oa":true,"landing_page_url":"https://doaj.org/article/af13b75d5b8142f7922bd86eaa20f444","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/5577486","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/5577486","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/5577486.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.75}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3145356632.pdf","grobid_xml":"https://content.openalex.org/works/W3145356632.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2013173480","https://openalex.org/W2034710737","https://openalex.org/W2128733372","https://openalex.org/W2413365859","https://openalex.org/W2558527411","https://openalex.org/W2559671899","https://openalex.org/W2790196784","https://openalex.org/W2807037009","https://openalex.org/W2906417655","https://openalex.org/W2921211943","https://openalex.org/W2921793324","https://openalex.org/W2939302023","https://openalex.org/W2942629287","https://openalex.org/W2978614058","https://openalex.org/W2989589623","https://openalex.org/W2991616984","https://openalex.org/W2996025019","https://openalex.org/W2997264611","https://openalex.org/W2999178925","https://openalex.org/W3034142796","https://openalex.org/W3034504400","https://openalex.org/W3037686265","https://openalex.org/W3044995911","https://openalex.org/W3046491228","https://openalex.org/W3082841960","https://openalex.org/W3097090744","https://openalex.org/W3111974190","https://openalex.org/W3116421301"],"related_works":["https://openalex.org/W2129863591","https://openalex.org/W1596769710","https://openalex.org/W2923497059","https://openalex.org/W2978363435","https://openalex.org/W3217448422","https://openalex.org/W2351279712","https://openalex.org/W1548888553","https://openalex.org/W2908249560","https://openalex.org/W3103207359","https://openalex.org/W2069475801"],"abstract_inverted_index":{"Music":[0],"classification":[1,12,27,33,47,72,139,182,214,225],"is":[2,57,135,147,167,215],"conducive":[3],"to":[4,17,38,82,119,165],"online":[5],"music":[6,11,32,43,46,63,75,87,96,127,181,191,198,206,213,224],"retrieval,":[7],"but":[8,156],"the":[9,26,30,40,62,71,74,84,90,93,121,124,131,138,142,152,157,173,187,195,220],"current":[10,31,180],"model":[13,34,48,125,146,185],"finds":[14],"it":[15,134],"difficult":[16],"accurately":[18],"identify":[19,202],"various":[20,68,203],"types":[21,204],"of":[22,29,42,73,86,123,141,151,159,172,189,197,205,212,222],"music,":[23],"which":[24,218],"makes":[25],"effect":[28],"poor.":[35],"In":[36],"order":[37],"improve":[39],"accuracy":[41,140,164,211],"classification,":[44,199],"a":[45],"based":[49],"on":[50],"multifeature":[51],"fusion":[52],"and":[53,65,77,89,98,200],"machine":[54,79,102],"learning":[55,80,103],"algorithm":[56],"proposed.":[58],"First,":[59],"we":[60],"obtain":[61],"signal,":[64,76],"then":[66],"extract":[67],"features":[69],"from":[70],"use":[78],"algorithms":[81],"describe":[83],"type":[85],"signal":[88],"relationship":[91],"between":[92],"features.":[94],"The":[95,210],"classifier":[97],"deep":[99,143],"belief":[100],"network":[101,145],"models":[104,118],"in":[105],"shallow":[106],"logistic":[107,153,174],"regression":[108,154,175],"are":[109],"established,":[110],"respectively.":[111],"Experiments":[112],"were":[113],"designed":[114],"for":[115,126,162],"these":[116],"two":[117],"verify":[120],"applicability":[122],"classification.":[128],"By":[129],"comparing":[130],"experimental":[132],"results,":[133],"found":[136],"that":[137,150,171],"confidence":[144],"higher":[148,169],"than":[149,170],"model,":[155],"number":[158],"iterations":[160],"needed":[161],"its":[163],"converge":[166],"also":[168],"model.":[176,226],"Compared":[177],"with":[178,207],"other":[179],"models,":[183],"this":[184,223],"reduces":[186],"time":[188],"constructing":[190],"classifier,":[192],"speeds":[193],"up":[194],"speed":[196],"can":[201],"high":[208],"precision.":[209],"obviously":[216],"improved,":[217],"verifies":[219],"superiority":[221]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}