{"id":"https://openalex.org/W4323521086","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10051897","title":"Structured Model Selection for Recovery of Sparse Representations in Nested Periodic Dictionaries","display_name":"Structured Model Selection for Recovery of Sparse Representations in Nested Periodic Dictionaries","publication_year":2022,"publication_date":"2022-10-31","ids":{"openalex":"https://openalex.org/W4323521086","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10051897"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf56349.2022.10051897","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ieeeconf56349.2022.10051897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","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/A5037985191","display_name":"Pouria Saidi","orcid":"https://orcid.org/0000-0001-7583-9722"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pouria Saidi","raw_affiliation_strings":["School of Electrical, Computer and Energy Engineering, Arizona State University,Tempe,AZ,USA,85281"],"affiliations":[{"raw_affiliation_string":"School of Electrical, Computer and Energy Engineering, Arizona State University,Tempe,AZ,USA,85281","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003612688","display_name":"George Atia","orcid":"https://orcid.org/0000-0001-7958-9855"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George K. Atia","raw_affiliation_strings":["University of Central Florida,Department of Electrical and Computer Engineering, Department of Computer Science,Orlando,FL,USA,32816"],"affiliations":[{"raw_affiliation_string":"University of Central Florida,Department of Electrical and Computer Engineering, Department of Computer Science,Orlando,FL,USA,32816","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037985191"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18258615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"862","last_page":"866"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994999766349792,"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":0.9970999956130981,"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/matching-pursuit","display_name":"Matching pursuit","score":0.816644549369812},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7727985382080078},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.742551863193512},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6552450656890869},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.5536122918128967},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5142483115196228},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5028104186058044},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4734487235546112},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35729068517684937},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34185004234313965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33916789293289185},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.31972265243530273}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.816644549369812},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7727985382080078},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.742551863193512},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6552450656890869},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.5536122918128967},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5142483115196228},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5028104186058044},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4734487235546112},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35729068517684937},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34185004234313965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33916789293289185},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.31972265243530273},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf56349.2022.10051897","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ieeeconf56349.2022.10051897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.800000011920929,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4439686520","display_name":null,"funder_award_id":"CCF-2106339","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1531869541","https://openalex.org/W1989009613","https://openalex.org/W1992905402","https://openalex.org/W2036437934","https://openalex.org/W2096506203","https://openalex.org/W2099100030","https://openalex.org/W2116148865","https://openalex.org/W2128659236","https://openalex.org/W2160979406","https://openalex.org/W2162800060","https://openalex.org/W2163067280","https://openalex.org/W2471468177","https://openalex.org/W2518032679","https://openalex.org/W2754518759","https://openalex.org/W2792870938","https://openalex.org/W2964041511","https://openalex.org/W3215277225","https://openalex.org/W4286894521","https://openalex.org/W4292088435","https://openalex.org/W6802684538"],"related_works":["https://openalex.org/W2098521117","https://openalex.org/W4319793311","https://openalex.org/W2465351041","https://openalex.org/W4385694579","https://openalex.org/W2340242818","https://openalex.org/W4300881421","https://openalex.org/W2103001330","https://openalex.org/W2012574959","https://openalex.org/W2262109992","https://openalex.org/W2241396314"],"abstract_inverted_index":{"Periodic":[0],"signals":[1,25],"were":[2],"shown":[3],"to":[4,20,47],"admit":[5],"sparse":[6,14,29,36],"representations":[7,30],"in":[8,24,31,60,126],"Nested":[9],"periodic":[10,63,78,83],"dictionaries":[11],"(NPDs).":[12],"Therefore,":[13],"recovery":[15,37,121],"frameworks":[16],"have":[17],"been":[18],"employed":[19],"estimate":[21],"the":[22,48,51,89,100],"periodicity":[23],"by":[26],"finding":[27],"their":[28,57],"such":[32,39],"dictionaries.":[33],"However,":[34],"existing":[35],"algorithms":[38,71,122],"as":[40,54],"Orthogonal":[41],"Matching":[42],"Pursuit":[43],"(OMP)":[44],"are":[45],"oblivious":[46],"structure":[49,92],"of":[50,96,102],"dictionary,":[52],"and":[53,81,93,108,111],"a":[55],"result":[56],"performance":[58,101,118],"degrade":[59],"settings":[61],"involving":[62],"mixtures.":[64],"In":[65],"this":[66],"work,":[67],"we":[68],"propose":[69],"new":[70],"for":[72],"structured":[73],"model":[74],"selection,":[75],"termed":[76],"nested":[77,82],"subspace":[79,84],"OMP":[80],"regularized":[85],"OMP,":[86],"that":[87,113],"leverage":[88],"well-known":[90],"Euler":[91],"LCM":[94],"property":[95],"NPDs.":[97],"We":[98],"evaluate":[99],"these":[103],"methods":[104],"using":[105],"both":[106],"synthesized":[107],"real":[109],"data":[110],"show":[112],"they":[114],"can":[115],"yield":[116],"better":[117],"than":[119],"generic":[120],"while":[123],"also":[124],"saving":[125],"computation":[127],"time.":[128]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}