{"id":"https://openalex.org/W2592829360","doi":"https://doi.org/10.1109/acssc.2016.7869528","title":"Robust phase retrieval with sparsity under nonnegativity constraints","display_name":"Robust phase retrieval with sparsity under nonnegativity constraints","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2592829360","doi":"https://doi.org/10.1109/acssc.2016.7869528","mag":"2592829360"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2016.7869528","doi":"https://doi.org/10.1109/acssc.2016.7869528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2016.7869528","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"Asilomar Conference on Signals, Systems and Computers (ACSSC)","issn_l":"1058-6393","issn":["1058-6393","2576-2303"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 50th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5006764308","display_name":"Daniel S. Weller","orcid":"https://orcid.org/0000-0001-9818-7325","observed_orcids":["https://orcid.org/0000-0001-9818-7325"]},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daniel S. Weller","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006764308"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26918369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"1043","last_page":"1047"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9696999788284302,"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":0.9696999788284302,"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":0.015799999237060547,"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/T11183","display_name":"Advanced X-ray Imaging Techniques","score":0.0024999999441206455,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/phase-retrieval","display_name":"phase retrieval","score":0.949999988079071},{"id":"https://openalex.org/keywords/sparsity","display_name":"sparsity","score":0.8339999914169312},{"id":"https://openalex.org/keywords/non-negativity-constraints","display_name":"nonnegativity constraints","score":0.9919999837875366},{"id":"https://openalex.org/keywords/variable-splitting","display_name":"variable splitting","score":0.828000009059906},{"id":"https://openalex.org/keywords/alternating-optimization","display_name":"alternating optimization","score":0.9919999837875366},{"id":"https://openalex.org/keywords/1-norm-regularization","display_name":"1-norm regularization","score":0.7870000004768372},{"id":"https://openalex.org/keywords/hermitian-symmetry","display_name":"Hermitian symmetry","score":0.9490000009536743},{"id":"https://openalex.org/keywords/shepp-logan-phantom","display_name":"Shepp-Logan phantom","score":0.7940000295639038},{"id":"https://openalex.org/keywords/high-resolution-imaging","display_name":"high-resolution imaging","score":0.5809999704360962}],"concepts":[{"id":"https://openalex.org/C81793267","wikidata":"https://www.wikidata.org/wiki/Q7180962","display_name":"Phase retrieval","level":3,"score":0.7664445638656616},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5996382832527161},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5828477144241333},{"id":"https://openalex.org/C94940","wikidata":"https://www.wikidata.org/wiki/Q652941","display_name":"Hermitian matrix","level":2,"score":0.5433621406555176},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.505836009979248},{"id":"https://openalex.org/C2780016784","wikidata":"https://www.wikidata.org/wiki/Q2714507","display_name":"Orthant","level":2,"score":0.46186429262161255},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.45400476455688477},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4476074278354645},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.43941184878349304},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42788878083229065},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4216099679470062},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.41909900307655334},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4157659113407135},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.41499099135398865},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3444085717201233},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.30942708253860474},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2655928134918213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26305660605430603},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.11679437756538391},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/acssc.2016.7869528","doi":"https://doi.org/10.1109/acssc.2016.7869528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2016.7869528","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"Asilomar Conference on Signals, Systems and Computers (ACSSC)","issn_l":"1058-6393","issn":["1058-6393","2576-2303"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 50th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W136966946","https://openalex.org/W1980003430","https://openalex.org/W2001613283","https://openalex.org/W2007593159","https://openalex.org/W2045079045","https://openalex.org/W2058532290","https://openalex.org/W2080567893","https://openalex.org/W2128763644","https://openalex.org/W2133665775","https://openalex.org/W2135161976","https://openalex.org/W2145080587","https://openalex.org/W2163916252","https://openalex.org/W2164278908","https://openalex.org/W2224829387","https://openalex.org/W2244987555","https://openalex.org/W2342960679","https://openalex.org/W2950515139","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W2342960679","https://openalex.org/W7099446353","https://openalex.org/W4311544914","https://openalex.org/W136966946","https://openalex.org/W2051573259","https://openalex.org/W3013665705","https://openalex.org/W2532059923","https://openalex.org/W7155385837","https://openalex.org/W4319876722","https://openalex.org/W2793508829"],"abstract_inverted_index":{"High-resolution":[0],"phase":[1,83],"retrieval":[2,84],"is":[3],"challenging":[4],"due":[5],"to":[6,21,39],"the":[7,64,68,86],"low":[8],"signal-to-noise":[9],"ratio":[10],"of":[11,92],"measurements.":[12,45,97],"This":[13],"work":[14],"utilizes":[15],"variable":[16],"splitting":[17],"and":[18,33,51,62,95],"alternating":[19],"minimization":[20],"simultaneously":[22],"enforce":[23],"a":[24,90],"1-norm":[25],"data":[26],"fit":[27],"penalty,":[28],"an":[29,41],"analysis-form":[30,81],"sparse":[31,82],"regularizer,":[32],"nonnegativity":[34,52],"or":[35],"real-valued":[36,50],"image":[37,42,66,75],"constraints":[38,53],"resolve":[40],"from":[43],"squared-magnitude":[44],"The":[46,71],"reconstruction":[47],"algorithm":[48],"incorporates":[49],"via":[54],"enforcing":[55],"Hermitian":[56],"symmetry":[57],"on":[58,85],"Fourier":[59],"transform":[60],"coefficients":[61],"projecting":[63],"reconstructed":[65],"onto":[67],"nonnegative":[69],"orthant.":[70],"proposed":[72],"method":[73],"preserves":[74],"quality":[76],"more":[77],"robustly":[78],"than":[79],"unconstrained":[80],"Shepp-Logan":[87],"phantom,":[88],"for":[89],"range":[91],"noise":[93],"levels":[94],"outlier":[96]},"counts_by_year":[],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2017-03-16T00:00:00"}
