{"id":"https://openalex.org/W4407937670","doi":"https://doi.org/10.1109/access.2025.3545558","title":"Polynomial Phase Signal Denoising via Sparse Representations Over a SMAF-Based Dictionary Learning Algorithm","display_name":"Polynomial Phase Signal Denoising via Sparse Representations Over a SMAF-Based Dictionary Learning Algorithm","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407937670","doi":"https://doi.org/10.1109/access.2025.3545558"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3545558","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3545558","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3545558","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051501918","display_name":"Guojian Ou","orcid":"https://orcid.org/0000-0002-6769-1059"},"institutions":[{"id":"https://openalex.org/I4210119012","display_name":"Xichang University","ror":"https://ror.org/02h3fyk31","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119012"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guojian Ou","raw_affiliation_strings":["College of Information Technology, Xichang University, Xichang, Sichuan, China"],"raw_orcid":"https://orcid.org/0000-0002-6769-1059","affiliations":[{"raw_affiliation_string":"College of Information Technology, Xichang University, Xichang, Sichuan, China","institution_ids":["https://openalex.org/I4210119012"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111225369","display_name":"Chenping Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119012","display_name":"Xichang University","ror":"https://ror.org/02h3fyk31","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119012"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenping Zeng","raw_affiliation_strings":["College of Information Technology, Xichang University, Xichang, Sichuan, China"],"raw_orcid":"https://orcid.org/0000-0002-7746-2479","affiliations":[{"raw_affiliation_string":"College of Information Technology, Xichang University, Xichang, Sichuan, China","institution_ids":["https://openalex.org/I4210119012"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100960414","display_name":"Jiaqiang Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119012","display_name":"Xichang University","ror":"https://ror.org/02h3fyk31","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119012"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqiang Dong","raw_affiliation_strings":["College of Information Technology, Xichang University, Xichang, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0005-8562-1483","affiliations":[{"raw_affiliation_string":"College of Information Technology, Xichang University, Xichang, Sichuan, China","institution_ids":["https://openalex.org/I4210119012"]}]},{"author_position":"last","author":{"id":null,"display_name":"Die Han","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119012","display_name":"Xichang University","ror":"https://ror.org/02h3fyk31","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119012"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Die Han","raw_affiliation_strings":["College of Information Technology, Xichang University, Xichang, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Technology, Xichang University, Xichang, Sichuan, China","institution_ids":["https://openalex.org/I4210119012"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210119012"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.6419,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78168619,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"13","issue":null,"first_page":"38268","last_page":"38281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9966999888420105,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9966999888420105,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10638","display_name":"Optical measurement and interference techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6028966307640076},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5745691657066345},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.547383725643158},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.5365687608718872},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5331795811653137},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4688754081726074},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4670008420944214},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4137662947177887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4081016778945923},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3378012776374817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2445167899131775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6028966307640076},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5745691657066345},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.547383725643158},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.5365687608718872},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5331795811653137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4688754081726074},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4670008420944214},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4137662947177887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4081016778945923},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3378012776374817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2445167899131775},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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":2,"locations":[{"id":"doi:10.1109/access.2025.3545558","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3545558","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ffdcbf11eb5a4c7f8c5ec6be021e7a8e","is_oa":true,"landing_page_url":"https://doaj.org/article/ffdcbf11eb5a4c7f8c5ec6be021e7a8e","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":"IEEE Access, Vol 13, Pp 38268-38281 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3545558","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3545558","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G440555167","display_name":null,"funder_award_id":"KJQN202203112","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G6134553613","display_name":null,"funder_award_id":"117281669","funder_id":"https://openalex.org/F4320321135","funder_display_name":"Chongqing University"},{"id":"https://openalex.org/G98084660","display_name":null,"funder_award_id":"KJQN202303108","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"}],"funders":[{"id":"https://openalex.org/F4320321135","display_name":"Chongqing University","ror":"https://ror.org/023rhb549"},{"id":"https://openalex.org/F4320324805","display_name":"Chongqing Municipal Education Commission","ror":"https://ror.org/031nm5713"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2059311958","https://openalex.org/W2094829381","https://openalex.org/W2115985534","https://openalex.org/W2122969373","https://openalex.org/W2151693816","https://openalex.org/W2153663612","https://openalex.org/W2160547390","https://openalex.org/W2167188281","https://openalex.org/W2348177596","https://openalex.org/W2362066488","https://openalex.org/W2367435646","https://openalex.org/W2370887489","https://openalex.org/W2384778437","https://openalex.org/W2389119868","https://openalex.org/W2560042709","https://openalex.org/W2803333369","https://openalex.org/W2889146164","https://openalex.org/W2914177635","https://openalex.org/W2972205912","https://openalex.org/W3000631106","https://openalex.org/W3000696348","https://openalex.org/W3008537012","https://openalex.org/W3123987869","https://openalex.org/W3195891501","https://openalex.org/W4323041537","https://openalex.org/W4360612164","https://openalex.org/W4377244739","https://openalex.org/W4385480741","https://openalex.org/W4403338774","https://openalex.org/W6754321905"],"related_works":["https://openalex.org/W2369564042","https://openalex.org/W2390140919","https://openalex.org/W2509955295","https://openalex.org/W2126683262","https://openalex.org/W1987225540","https://openalex.org/W2363993830","https://openalex.org/W1778286912","https://openalex.org/W2116933539","https://openalex.org/W2561456314","https://openalex.org/W2249096836"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,52,67,122,141],"address":[4],"the":[5,34,62,69,74,86,90,94,99,106,125,128,138,144,149],"problem":[6],"of":[7,47,98,127,146],"denoising":[8,120],"polynomial":[9],"phase":[10],"signals":[11],"(PPS)":[12],"by":[13],"removing":[14],"additive":[15],"white":[16],"Gaussian":[17],"noise.":[18],"Our":[19],"approach":[20],"is":[21,31,109],"based":[22],"on":[23,137],"sparse":[24,103],"representation":[25,104],"using":[26,102,130],"a":[27],"trained":[28,64],"dictionary,":[29],"which":[30],"obtained":[32],"through":[33],"secondary":[35],"moving":[36,150],"average":[37,151],"filtering":[38],"(SMAF)":[39],"dictionary":[40,57,75,108],"learning":[41,58],"algorithm.":[42,135],"The":[43],"proposed":[44,132],"algorithm":[45],"consists":[46],"two":[48],"main":[49],"steps:":[50],"first,":[51],"utilize":[53],"K-SVD":[54,114],"or":[55],"other":[56],"algorithms":[59],"to":[60,72,79,113],"obtain":[61],"initial":[63],"dictionary;":[65],"second,":[66],"apply":[68],"SMAF":[70],"method":[71],"modify":[73],"atoms,":[76],"enabling":[77],"them":[78],"behave":[80],"more":[81],"smoothly":[82],"and":[83,115],"effectively":[84],"reducing":[85],"noise":[87],"present":[88],"in":[89],"atomic":[91],"structures.":[92],"Consequently,":[93],"signal-to-noise":[95],"ratio":[96],"(SNR)":[97],"reconstructed":[100],"signal":[101],"over":[105],"refined":[107],"significantly":[110],"improved":[111],"compared":[112],"RLS-DLA.":[116],"To":[117],"achieve":[118],"optimal":[119],"effectiveness,":[121],"first":[123],"estimate":[124],"SNR":[126,133],"PPS":[129],"our":[131],"estimation":[134],"Based":[136],"estimated":[139],"SNR,":[140],"then":[142],"determine":[143],"number":[145],"samples":[147],"for":[148],"filter":[152],"impulse":[153],"response.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}