{"id":"https://openalex.org/W2990357236","doi":"https://doi.org/10.1109/isncc.2019.8909190","title":"Blind Source Separation Via Geometric Segmentation with Canonical Correlation Analysis in Satellite Communications","display_name":"Blind Source Separation Via Geometric Segmentation with Canonical Correlation Analysis in Satellite Communications","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2990357236","doi":"https://doi.org/10.1109/isncc.2019.8909190","mag":"2990357236"},"language":"en","primary_location":{"id":"doi:10.1109/isncc.2019.8909190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isncc.2019.8909190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Symposium on Networks, Computers and Communications (ISNCC)","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/A5101580560","display_name":"Chengjie Li","orcid":"https://orcid.org/0000-0001-8352-8393"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengjie Li","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101719304","display_name":"Lidong Zhu","orcid":"https://orcid.org/0000-0002-3737-9435"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lidong Zhu","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100406038","display_name":"Zhen Zhang","orcid":"https://orcid.org/0000-0002-9139-0440"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Zhang","raw_affiliation_strings":["College of Computer Science, Sichuan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3338,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57934141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"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":1.0,"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":0.9702000021934509,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9682999849319458,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.8297826051712036},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.7014485001564026},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6714661121368408},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6562082767486572},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5681764483451843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.548291802406311},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5386365056037903},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4453679323196411},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4345543384552002},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.4275778532028198},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.42601633071899414},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4165898859500885},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.41264018416404724},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34713178873062134},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2781771421432495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09006375074386597},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08495977520942688},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06745877861976624},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06493091583251953}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.8297826051712036},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.7014485001564026},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6714661121368408},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6562082767486572},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5681764483451843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.548291802406311},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5386365056037903},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4453679323196411},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4345543384552002},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.4275778532028198},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.42601633071899414},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4165898859500885},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.41264018416404724},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34713178873062134},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2781771421432495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09006375074386597},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08495977520942688},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06745877861976624},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06493091583251953},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isncc.2019.8909190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isncc.2019.8909190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Symposium on Networks, Computers and Communications (ISNCC)","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":16,"referenced_works":["https://openalex.org/W1601553748","https://openalex.org/W1970712846","https://openalex.org/W2013294521","https://openalex.org/W2025341678","https://openalex.org/W2099741732","https://openalex.org/W2136353084","https://openalex.org/W2139457438","https://openalex.org/W2148788318","https://openalex.org/W2152355934","https://openalex.org/W2154021490","https://openalex.org/W2163749565","https://openalex.org/W2167083368","https://openalex.org/W2796809853","https://openalex.org/W2900193606","https://openalex.org/W4362515305","https://openalex.org/W6643066408"],"related_works":["https://openalex.org/W2390344110","https://openalex.org/W2046761971","https://openalex.org/W2364896863","https://openalex.org/W2361066326","https://openalex.org/W2182042810","https://openalex.org/W2156932837","https://openalex.org/W2380698615","https://openalex.org/W374502268","https://openalex.org/W2103029460","https://openalex.org/W1785857632"],"abstract_inverted_index":{"In":[0,21],"this":[1,42],"paper,":[2],"we":[3,25,79],"consider":[4],"a":[5,45,59],"simple":[6],"and":[7,87],"effective":[8],"blind":[9],"source":[10,55],"separation":[11],"(BSS)":[12],"method":[13,86,91],"based":[14,52,92],"on":[15,53,93],"geometric":[16,23],"segmentation":[17],"in":[18,41],"satellite":[19],"communications.":[20],"the":[22,27,54,71,81,84,89,100,103],"segmentation,":[24],"analyze":[26],"correlation":[28,35,75],"between":[29],"any":[30],"two":[31,39],"vectors":[32],"with":[33],"canonical":[34,74],"analysis.":[36,76],"There":[37],"are":[38],"contributions":[40],"paper.":[43],"Firstly,":[44],"three-dimensional":[46],"geometrical":[47,61],"hybrid":[48,62],"model":[49,63],"is":[50,67],"proposed":[51,68,85,104],"signal's":[56],"sparseness.":[57],"Secondly,":[58],"novel":[60,90],"of":[64,73,83,102],"feature":[65],"extraction":[66],"according":[69],"to":[70],"idea":[72],"At":[77],"last,":[78],"discuss":[80],"performance":[82],"verify":[88],"several":[94],"simulations.":[95],"The":[96],"experimental":[97],"results":[98],"demonstrate":[99],"effectiveness":[101],"method.":[105]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}