{"id":"https://openalex.org/W2953884129","doi":"https://doi.org/10.1109/icnsc.2019.8743171","title":"Sparse component analysis based on an improved ant K-means clustering algorithm for underdetermined blind source separation","display_name":"Sparse component analysis based on an improved ant K-means clustering algorithm for underdetermined blind source separation","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2953884129","doi":"https://doi.org/10.1109/icnsc.2019.8743171","mag":"2953884129"},"language":"en","primary_location":{"id":"doi:10.1109/icnsc.2019.8743171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnsc.2019.8743171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC)","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/A5101917656","display_name":"Shuang Wei","orcid":"https://orcid.org/0000-0002-6250-6926"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuang Wei","raw_affiliation_strings":["College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669010","display_name":"Feng Wang","orcid":"https://orcid.org/0000-0002-2378-9126"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wang","raw_affiliation_strings":["Array and Information Processing Laboratory, Hohai University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Array and Information Processing Laboratory, Hohai University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031903832","display_name":"Defu Jiang","orcid":"https://orcid.org/0000-0001-7639-0496"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defu Jiang","raw_affiliation_strings":["Array and Information Processing Laboratory, Hohai University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Array and Information Processing Laboratory, Hohai University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I163340411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101917656"],"corresponding_institution_ids":["https://openalex.org/I21945476"],"apc_list":null,"apc_paid":null,"fwci":0.8293,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.72578863,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"5","issue":null,"first_page":"200","last_page":"205"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/underdetermined-system","display_name":"Underdetermined system","score":0.8195316791534424},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7897350788116455},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.769743800163269},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7088860869407654},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.6107860803604126},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.5557622909545898},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5209128260612488},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5156630277633667},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4879011809825897},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.47190552949905396},{"id":"https://openalex.org/keywords/component-analysis","display_name":"Component analysis","score":0.4478533864021301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44747844338417053},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.4187988042831421},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.3564864993095398},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.11249634623527527}],"concepts":[{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.8195316791534424},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7897350788116455},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.769743800163269},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7088860869407654},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.6107860803604126},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.5557622909545898},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5209128260612488},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5156630277633667},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4879011809825897},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.47190552949905396},{"id":"https://openalex.org/C2780692498","wikidata":"https://www.wikidata.org/wiki/Q16950721","display_name":"Component analysis","level":2,"score":0.4478533864021301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44747844338417053},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.4187988042831421},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3564864993095398},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.11249634623527527},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnsc.2019.8743171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnsc.2019.8743171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W138813470","https://openalex.org/W1485391971","https://openalex.org/W2025118363","https://openalex.org/W2031583051","https://openalex.org/W2038237443","https://openalex.org/W2076528385","https://openalex.org/W2118051273","https://openalex.org/W2127271355","https://openalex.org/W2151186643","https://openalex.org/W2159444579","https://openalex.org/W2162356910","https://openalex.org/W2377792686","https://openalex.org/W2497387515","https://openalex.org/W6605639775","https://openalex.org/W7038447206"],"related_works":["https://openalex.org/W2383973401","https://openalex.org/W2095924515","https://openalex.org/W2351680970","https://openalex.org/W2030887432","https://openalex.org/W2900617041","https://openalex.org/W2206857820","https://openalex.org/W2375962929","https://openalex.org/W2034312940","https://openalex.org/W2113403277","https://openalex.org/W1598723711"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposed":[2,38,89,112],"an":[3,42],"improved":[4,43,76,103],"sparse":[5,29],"component":[6],"analysis":[7],"(SCA)":[8],"approach":[9,40,91,114],"to":[10,26,52,67,92],"improve":[11],"the":[12,20,24,37,54,69,75,81,88,102,106,111,119],"performance":[13],"of":[14,98],"underdetermined":[15],"blind":[16,121],"source":[17,122],"separation":[18],"for":[19,31,87,117],"acoustic/speech":[21,32],"sources.":[22],"First,":[23],"pre-processing":[25],"build":[27],"a":[28,59,94],"model":[30],"sources":[33],"is":[34],"described.":[35],"Then,":[36],"SCA":[39,90,113],"designs":[41],"K-means":[44],"clustering":[45,77],"algorithm":[46,51,66,78],"based":[47,61],"on":[48,62],"ant":[49],"colony":[50],"estimate":[53],"mixture":[55,99],"matrix,":[56,100],"and":[57,101],"utilize":[58],"method":[60,104],"orthogonal":[63],"matching":[64],"pursuit":[65],"re-cover":[68],"signals.":[70,123],"Experiment":[71],"results":[72],"demonstrate":[73],"that":[74],"can":[79,109],"enhance":[80],"global":[82],"searching":[83],"ability":[84],"which":[85],"benefits":[86],"achieve":[93],"higher":[95],"estimation":[96],"accuracy":[97],"in":[105],"second":[107],"step":[108],"make":[110],"work":[115],"well":[116],"recovering":[118],"multi-channel":[120]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
