{"id":"https://openalex.org/W2133911706","doi":"https://doi.org/10.1109/icassp.2009.4960325","title":"Energy-constrained discriminant analysis","display_name":"Energy-constrained discriminant analysis","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2133911706","doi":"https://doi.org/10.1109/icassp.2009.4960325","mag":"2133911706"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4960325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1721.1/60231","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004694824","display_name":"Scott Philips","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Scott Philips","raw_affiliation_strings":["MIT Lincoln Laboratories, Lexington, MA, USA","MIT Lincoln Laboratory, 244 Wood Street, Lexington, MA 02420 USA"],"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratories, Lexington, MA, USA","institution_ids":["https://openalex.org/I4210122954"]},{"raw_affiliation_string":"MIT Lincoln Laboratory, 244 Wood Street, Lexington, MA 02420 USA","institution_ids":["https://openalex.org/I4210122954"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021646973","display_name":"Visar Berisha","orcid":"https://orcid.org/0000-0001-8804-8874"},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Visar Berisha","raw_affiliation_strings":["MIT Lincoln Laboratories, Lexington, MA, USA","MIT Lincoln Laboratory, 244 Wood Street, Lexington, MA 02420 USA"],"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratories, Lexington, MA, USA","institution_ids":["https://openalex.org/I4210122954"]},{"raw_affiliation_string":"MIT Lincoln Laboratory, 244 Wood Street, Lexington, MA 02420 USA","institution_ids":["https://openalex.org/I4210122954"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074371899","display_name":"Andreas Spanias","orcid":"https://orcid.org/0000-0003-0306-9348"},"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":false,"raw_author_name":"Andreas Spanias","raw_affiliation_strings":["Department of Electrical Engineering, Arizona State University, Tempe, AZ, USA","Arizona State University, Department of Electrical Engineering, Box 5706, Tempe, 85287 USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University, Department of Electrical Engineering, Box 5706, Tempe, 85287 USA#TAB#","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004694824"],"corresponding_institution_ids":["https://openalex.org/I4210122954"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.17025765,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"27","issue":null,"first_page":"3281","last_page":"3284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9943000078201294,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9943000078201294,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.992900013923645,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/overfitting","display_name":"Overfitting","score":0.912753701210022},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.8289622068405151},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6853864789009094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6702041029930115},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6593406200408936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6147096157073975},{"id":"https://openalex.org/keywords/optimal-discriminant-analysis","display_name":"Optimal discriminant analysis","score":0.529131293296814},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5266088247299194},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5014474391937256},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4981043338775635},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.4601147770881653},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.44765153527259827},{"id":"https://openalex.org/keywords/multiple-discriminant-analysis","display_name":"Multiple discriminant analysis","score":0.44395801424980164},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3218942880630493},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3162519335746765},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23855730891227722},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1291293203830719},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12677985429763794}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.912753701210022},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.8289622068405151},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6853864789009094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6702041029930115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6593406200408936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6147096157073975},{"id":"https://openalex.org/C104500394","wikidata":"https://www.wikidata.org/wiki/Q17104912","display_name":"Optimal discriminant analysis","level":3,"score":0.529131293296814},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5266088247299194},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5014474391937256},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4981043338775635},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.4601147770881653},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.44765153527259827},{"id":"https://openalex.org/C58596280","wikidata":"https://www.wikidata.org/wiki/Q28324849","display_name":"Multiple discriminant analysis","level":3,"score":0.44395801424980164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3218942880630493},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3162519335746765},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23855730891227722},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1291293203830719},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12677985429763794},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2009.4960325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/60231","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/60231","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/60231","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/60231","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1639032689","https://openalex.org/W1967073510","https://openalex.org/W2001619934","https://openalex.org/W2010853190","https://openalex.org/W2024060531","https://openalex.org/W2068276287","https://openalex.org/W2072184377","https://openalex.org/W2097571405","https://openalex.org/W2121647436","https://openalex.org/W2129476886","https://openalex.org/W2134262590","https://openalex.org/W2146993988","https://openalex.org/W2148694408","https://openalex.org/W2161332479","https://openalex.org/W2182510773","https://openalex.org/W2536620281","https://openalex.org/W3023540311","https://openalex.org/W3133917342","https://openalex.org/W4243694527","https://openalex.org/W4250857377","https://openalex.org/W6723264532","https://openalex.org/W6776535907"],"related_works":["https://openalex.org/W2063246903","https://openalex.org/W2375208160","https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W1984472287","https://openalex.org/W2544441948","https://openalex.org/W2113920489","https://openalex.org/W4254976464","https://openalex.org/W1534459252","https://openalex.org/W2044228987"],"abstract_inverted_index":{"Dimensionality":[0],"reduction":[1],"algorithms":[2],"have":[3],"become":[4],"an":[5],"indispensable":[6],"tool":[7],"for":[8],"working":[9],"with":[10],"high-dimensional":[11,27],"data":[12,28,67],"in":[13,43,133,146],"classification.":[14],"Linear":[15],"discriminant":[16,102],"analysis":[17,22,103],"(LDA)":[18],"is":[19,40,56,155],"a":[20,30,98],"popular":[21],"technique":[23,39,131],"used":[24,42],"to":[25,90,139,162],"project":[26],"into":[29],"lower-dimensional":[31],"space":[32],"while":[33,120],"maximizing":[34],"class":[35],"separability.":[36],"Although":[37],"this":[38,94],"widely":[41],"many":[44],"applications,":[45],"it":[46],"suffers":[47],"from":[48],"overfitting":[49,70],"when":[50,137],"the":[51,58,62,65,72,75,86,107,129,153],"number":[52],"of":[53,64,74,109,148],"training":[54],"examples":[55],"on":[57],"same":[59],"order":[60],"as":[61],"dimension":[63],"original":[66],"space.":[68],"When":[69],"occurs,":[71],"direction":[73],"LDA":[76,110],"solution":[77,87],"can":[78,159],"be":[79,160],"dominated":[80],"by":[81,111],"low-energy":[82],"noise":[83],"and":[84,158],"therefore":[85],"becomes":[88],"non-robust":[89],"unseen":[91],"data.":[92],"In":[93],"paper,":[95],"we":[96],"propose":[97],"novel":[99],"algorithm,":[100],"energy-constrained":[101],"(ECDA),":[104],"that":[105,116,128],"overcomes":[106],"limitations":[108],"finding":[112],"lower":[113],"dimensional":[114],"projections":[115],"maximize":[117],"inter-class":[118],"separability,":[119],"also":[121],"preserving":[122],"signal":[123],"energy.":[124],"Our":[125],"results":[126,132,143],"show":[127],"proposed":[130],"higher":[134],"classification":[135,164],"rates":[136],"compared":[138],"comparable":[140],"methods.":[141],"The":[142],"are":[144],"given":[145],"terms":[147],"SAR":[149],"image":[150],"classification,":[151],"however":[152],"algorithm":[154],"broadly":[156],"applicable":[157],"generalized":[161],"any":[163],"problem.":[165]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}