{"id":"https://openalex.org/W2102283862","doi":"https://doi.org/10.1109/ijcnn.2004.1380944","title":"Training multilayer perceptron and radial basis function neural networks for wavefront sensing and restoration of turbulence-degraded imagery","display_name":"Training multilayer perceptron and radial basis function neural networks for wavefront sensing and restoration of turbulence-degraded imagery","publication_year":2005,"publication_date":"2005-01-31","ids":{"openalex":"https://openalex.org/W2102283862","doi":"https://doi.org/10.1109/ijcnn.2004.1380944","mag":"2102283862"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1380944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1380944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","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/A5004841177","display_name":"G.S. Chundi","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"G.S. Chundi","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of Arizona Tucson, Tucson, AZ, USA","[Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ, USA]"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of Arizona Tucson, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"[Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ, USA]","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084890499","display_name":"Michael Lloyd\u2010Hart","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]},{"id":"https://openalex.org/I4210122332","display_name":"Optical Sciences (United States)","ror":"https://ror.org/03122yk49","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122332"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Lloyd-Hart","raw_affiliation_strings":["Steward Observatory, University of Arizona Tucson, Tucson, AZ, USA","Optical Sciences, College of"],"affiliations":[{"raw_affiliation_string":"Steward Observatory, University of Arizona Tucson, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Optical Sciences, College of","institution_ids":["https://openalex.org/I4210122332"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066800063","display_name":"Malur K. Sundareshan","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M.K. Sundareshan","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of Arizona Tucson, Tucson, AZ, USA","University of Arizona"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of Arizona Tucson, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"University of Arizona","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004841177"],"corresponding_institution_ids":["https://openalex.org/I138006243"],"apc_list":null,"apc_paid":null,"fwci":0.9782,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.75894234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"3","issue":null,"first_page":"2117","last_page":"2122"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11484","display_name":"Adaptive optics and wavefront sensing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11484","display_name":"Adaptive optics and wavefront sensing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14158","display_name":"Optical Systems and Laser Technology","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11517","display_name":"Advanced optical system design","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6767407059669495},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6264929175376892},{"id":"https://openalex.org/keywords/wavefront","display_name":"Wavefront","score":0.544605553150177},{"id":"https://openalex.org/keywords/strehl-ratio","display_name":"Strehl ratio","score":0.5405996441841125},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.5405115485191345},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5251685976982117},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5084456205368042},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.493156373500824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4924224615097046},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.480476051568985},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4291716516017914},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4152531027793884},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3596450090408325},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18576553463935852},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11198094487190247},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08995887637138367}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6767407059669495},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6264929175376892},{"id":"https://openalex.org/C165699331","wikidata":"https://www.wikidata.org/wiki/Q461533","display_name":"Wavefront","level":2,"score":0.544605553150177},{"id":"https://openalex.org/C90416638","wikidata":"https://www.wikidata.org/wiki/Q1459394","display_name":"Strehl ratio","level":3,"score":0.5405996441841125},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.5405115485191345},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5251685976982117},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5084456205368042},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.493156373500824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4924224615097046},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.480476051568985},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4291716516017914},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4152531027793884},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3596450090408325},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18576553463935852},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11198094487190247},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08995887637138367},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2004.1380944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1380944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1484412996","https://openalex.org/W1900101064","https://openalex.org/W1986311150","https://openalex.org/W1987529851","https://openalex.org/W2048448689","https://openalex.org/W2051812123","https://openalex.org/W2059157514","https://openalex.org/W2069870625","https://openalex.org/W2074397823","https://openalex.org/W2166822322","https://openalex.org/W3010612091","https://openalex.org/W4246497077","https://openalex.org/W6628955290","https://openalex.org/W6684749109"],"related_works":["https://openalex.org/W2977982891","https://openalex.org/W2096715552","https://openalex.org/W4298111019","https://openalex.org/W4315435472","https://openalex.org/W1598419248","https://openalex.org/W2103292044","https://openalex.org/W4234515837","https://openalex.org/W2296440556","https://openalex.org/W2370830768","https://openalex.org/W2157934879"],"abstract_inverted_index":{"A":[0,74],"computationally":[1],"efficient":[2],"neural":[3,66,106,158,171],"network-based":[4],"scheme":[5,55],"for":[6,27,155],"wavefront":[7,120],"reconstruction":[8],"and":[9,93,112,124,152],"restoration":[10],"of":[11,30,46,61,77,82,90,138,141,167,170,177],"turbulence-degraded":[12],"imagery":[13],"in":[14,21,71,95,128,136,173],"Adaptive":[15],"Optics":[16],"(AO)-based":[17],"telescopes":[18],"is":[19,69,99,131],"described":[20,70,123],"this":[22,44,72],"paper.":[23],"Currently":[24],"popular":[25],"methods":[26,154],"the":[28,96,102,149,168],"estimation":[29],"turbulence-generated":[31],"distortions":[32],"suffer":[33],"from":[34],"high":[35],"computational":[36],"complexity":[37],"that":[38,56],"preclude":[39],"real-time":[40,175],"implementations.":[41],"For":[42],"overcoming":[43],"\"curse":[45],"dimensionality\",":[47],"a":[48,58,65,86,164],"discrete":[49],"cosine":[50],"transform":[51],"(DCT)-based":[52],"feature":[53],"extraction":[54],"provides":[57],"reduced":[59],"set":[60],"features":[62],"to":[63,79,118,148,157],"train":[64],"network":[67,107],"estimator":[68],"work.":[73],"dimensionality":[75],"reduction":[76],"up":[78],"two":[80],"orders":[81],"magnitude,":[83],"accompanied":[84],"by":[85,101],"relatively":[87],"insignificant":[88],"loss":[89],"overall":[91,97],"information,":[92],"consequently":[94],"performance,":[98],"achieved":[100],"proposed":[103],"scheme.":[104],"Two":[105],"architectures,":[108],"Multilayer":[109],"Perceptron":[110],"(MLP)":[111],"Radial":[113],"Basis":[114],"Function":[115],"(RBF),":[116],"trained":[117],"estimate":[119],"parameters":[121],"are":[122],"their":[125],"relative":[126],"performance":[127],"AO":[129],"implementations":[130],"outlined.":[132],"Performance":[133],"differences":[134,151],"measured":[135],"terms":[137],"specific":[139],"quantities":[140],"interest,":[142],"such":[143],"as":[144],"Strehl":[145],"ratio,":[146],"point":[147],"architectural":[150],"training":[153],"these":[156,178],"networks.":[159],"The":[160],"present":[161],"work":[162],"represents":[163],"novel":[165],"application":[166],"power":[169],"networks":[172],"facilitating":[174],"implementation":[176],"systems.":[179]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
