{"id":"https://openalex.org/W4412560789","doi":"https://doi.org/10.1109/mocast65744.2025.11083729","title":"Sparse-KSVD for Blind Decomposition on Task-Related FMRI Data: A Comparative Analysis with ICA and MCA-KSVD","display_name":"Sparse-KSVD for Blind Decomposition on Task-Related FMRI Data: A Comparative Analysis with ICA and MCA-KSVD","publication_year":2025,"publication_date":"2025-06-11","ids":{"openalex":"https://openalex.org/W4412560789","doi":"https://doi.org/10.1109/mocast65744.2025.11083729"},"language":"en","primary_location":{"id":"doi:10.1109/mocast65744.2025.11083729","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mocast65744.2025.11083729","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)","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/A5000656126","display_name":"Phuc Truong Loc Nguyen","orcid":"https://orcid.org/0000-0002-9423-7935"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]},{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Phuc Truong Loc Nguyen","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg","Technische Universität Dresden"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Technische Universität Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083465496","display_name":"P. Nguyen","orcid":"https://orcid.org/0009-0007-9117-3570"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]},{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Phuoc Khang Nguyen","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg","Technische Universität Dresden"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Technische Universität Dresden","institution_ids":["https://openalex.org/I78650965"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000656126"],"corresponding_institution_ids":["https://openalex.org/I181369854","https://openalex.org/I78650965"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20128973,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9836000204086304,"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":0.9836000204086304,"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":0.6532400846481323},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.5213509798049927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48585245013237},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43818244338035583},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4120984971523285},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37159574031829834},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.116879403591156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6532400846481323},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.5213509798049927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48585245013237},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43818244338035583},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4120984971523285},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37159574031829834},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.116879403591156},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mocast65744.2025.11083729","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mocast65744.2025.11083729","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)","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":20,"referenced_works":["https://openalex.org/W1986931325","https://openalex.org/W1993393316","https://openalex.org/W2058248579","https://openalex.org/W2058408209","https://openalex.org/W2095921032","https://openalex.org/W2099321050","https://openalex.org/W2103402739","https://openalex.org/W2116799974","https://openalex.org/W2140856955","https://openalex.org/W2151693816","https://openalex.org/W2159644148","https://openalex.org/W2160547390","https://openalex.org/W2212142588","https://openalex.org/W2526521822","https://openalex.org/W2608505488","https://openalex.org/W2752611890","https://openalex.org/W2796857673","https://openalex.org/W2951583631","https://openalex.org/W4226021119","https://openalex.org/W4236490297"],"related_works":["https://openalex.org/W2121429698","https://openalex.org/W2182042810","https://openalex.org/W4252230435","https://openalex.org/W55679925","https://openalex.org/W3080404860","https://openalex.org/W2046761971","https://openalex.org/W3144722888","https://openalex.org/W1564859343","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Functional":[0],"MRI":[1],"(fMRI)":[2],"data":[3],"analysis":[4,96],"enables":[5],"researchers":[6],"to":[7,82,108,138,148],"partition":[8],"the":[9,49,88],"brain":[10,33,76,103],"into":[11,17],"distinct":[12],"regions,":[13],"offering":[14],"valuable":[15],"insights":[16],"neurological":[18],"disorders.":[19],"A":[20],"widely":[21],"used":[22],"decomposition":[23],"technique":[24],"is":[25,79,134,146],"Independent":[26],"Component":[27],"Analysis":[28],"(ICA),":[29],"which":[30],"identifies":[31,101],"functional":[32,75,102],"networks":[34,104],"by":[35],"assuming":[36],"statistical":[37],"independence":[38],"between":[39],"components.":[40],"However,":[41,142],"this":[42,59],"assumption":[43],"may":[44],"not":[45],"fully":[46],"align":[47],"with":[48,66,105],"physiological":[50],"characteristics":[51],"of":[52,110],"fMRI":[53,71,93],"data.":[54,94],"To":[55],"address":[56],"these":[57],"limitations,":[58],"study":[60],"explores":[61],"Sparse-KSVD,":[62],"a":[63,135],"KSVD-based":[64],"method":[65],"limited":[67],"prior":[68],"application":[69],"in":[70,117],"research,":[72],"for":[73],"identifying":[74],"networks.":[77],"Sparse-KSVD":[78,115,133],"systematically":[80],"compared":[81],"MCAKSVD,":[83],"another":[84],"KSVD-family":[85],"method,":[86],"and":[87,112,122,140],"conventional":[89],"ICA":[90,111,139],"using":[91],"task-related":[92],"The":[95],"shows":[97],"that":[98,132],"SparseKSVD":[99],"accurately":[100],"results":[106],"comparable":[107],"those":[109],"MCA-KSVD.":[113,141],"Furthermore,":[114],"outperforms":[116],"execution":[118],"time,":[119],"signal":[120],"localization,":[121],"spatial":[123],"resolution":[124],"under":[125],"optimal":[126],"parameter":[127,144],"settings.":[128],"These":[129],"findings":[130],"demonstrate":[131],"promising":[136],"alternative":[137],"careful":[143],"tuning":[145],"essential":[147],"achieve":[149],"its":[150],"full":[151],"potential.":[152]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}