{"id":"https://openalex.org/W1587863748","doi":"https://doi.org/10.1109/icassp.1976.1170121","title":"Orthogonal transforms for digital signal processing","display_name":"Orthogonal transforms for digital signal processing","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W1587863748","doi":"https://doi.org/10.1109/icassp.1976.1170121","mag":"1587863748"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1976.1170121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1976.1170121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '76. IEEE International Conference on Acoustics, Speech, and Signal Processing","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/A5078861665","display_name":"K.R. Rao","orcid":"https://orcid.org/0000-0002-8513-3114"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. Rao","raw_affiliation_strings":["Department of Electrical Engineering, University of Texas, Arlington, Arlington, TX, USA","University of Texas at Arlington; Arlington; Texas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Texas, Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]},{"raw_affiliation_string":"University of Texas at Arlington; Arlington; Texas","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063287953","display_name":"N. Ahmed","orcid":"https://orcid.org/0000-0003-3049-0998"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"N. Ahmed","raw_affiliation_strings":["Department of Electrical Engineering, Kansas State University, Manhattan, KS, USA","Dept. of Electrical Eng., Kansas State Univ., Manhattan, KS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Kansas State University, Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]},{"raw_affiliation_string":"Dept. of Electrical Eng., Kansas State Univ., Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":33.4978,"has_fulltext":false,"cited_by_count":837,"citation_normalized_percentile":{"value":0.99848956,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"1","issue":null,"first_page":"136","last_page":"140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.995199978351593,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.995199978351593,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9943000078201294,"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/T10320","display_name":"Neural Networks and Applications","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.6845391988754272},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5681453347206116},{"id":"https://openalex.org/keywords/hadamard-transform","display_name":"Hadamard transform","score":0.5616433620452881},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5323987603187561},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.47870874404907227},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.46595460176467896},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.45275235176086426},{"id":"https://openalex.org/keywords/walsh-function","display_name":"Walsh function","score":0.4477510452270508},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.44555947184562683},{"id":"https://openalex.org/keywords/discrete-fourier-transform","display_name":"Discrete Fourier transform (general)","score":0.43587690591812134},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4128803610801697},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3956802189350128},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3186151683330536},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.29801931977272034},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.2552317976951599},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.135456383228302}],"concepts":[{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.6845391988754272},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5681453347206116},{"id":"https://openalex.org/C60292330","wikidata":"https://www.wikidata.org/wiki/Q1014065","display_name":"Hadamard transform","level":2,"score":0.5616433620452881},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5323987603187561},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.47870874404907227},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.46595460176467896},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.45275235176086426},{"id":"https://openalex.org/C164319782","wikidata":"https://www.wikidata.org/wiki/Q1934233","display_name":"Walsh function","level":2,"score":0.4477510452270508},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.44555947184562683},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.43587690591812134},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4128803610801697},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3956802189350128},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3186151683330536},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.29801931977272034},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.2552317976951599},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.135456383228302},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1976.1170121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1976.1170121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '76. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4385456289","https://openalex.org/W3100437958","https://openalex.org/W2011252634","https://openalex.org/W2303723627","https://openalex.org/W2150576912","https://openalex.org/W2513780272","https://openalex.org/W1983699456","https://openalex.org/W2074194659","https://openalex.org/W2086323236","https://openalex.org/W2963134360"],"abstract_inverted_index":{"A":[0],"tutorial-review":[1],"paper":[2],"on":[3,76],"discrete":[4,26,28,33],"orthogonal":[5],"transforms":[6,23,54,74,88,126],"and":[7,13,17,44,48,60,63,91,101,115,122,153],"their":[8],"applications":[9],"in":[10,89,129],"digital":[11,96,107,154],"signal":[12],"image":[14,92],"(both":[15],"monochrome":[16],"color)":[18],"processing":[19],"is":[20,118],"presented.":[21,83,119],"Various":[22],"such":[24,55,136],"as":[25,56,137],"Fourier,":[27],"cosine,":[29],"Walsh-Hadamard,":[30],"slant,":[31],"Haar,":[32,41],"linear":[34],"basis,":[35],"Hadamard-Haar,":[36],"rapid,":[37],"lower":[38],"triangular,":[39],"generalized":[40],"slant":[42],"Haar":[43],"Karhunen-Lo\u00eave":[45],"are":[46,65,82,127],"defined":[47],"developed.":[49],"Pertinent":[50],"properties":[51],"of":[52,72,86,124,131],"these":[53,73,87,125],"power":[57],"spectra,":[58],"cyclic":[59],"dyadic":[61],"convolution":[62],"correlation":[64],"outlined.":[66],"Efficient":[67],"algorithms":[68],"for":[69],"fast":[70],"implementation":[71],"based":[75],"matrix":[77,80],"partitioning":[78],"or":[79],"factoring":[81],"The":[84,120],"application":[85],"speech":[90],"processing,":[93],"spectral":[94],"analysis,":[95,105],"filtering":[97],"(linear,":[98],"nonlinear,":[99],"optimal":[100],"suboptimal),":[102],"nonlinear":[103],"systems":[104],"spectrography,":[106],"holography,":[108],"industrial":[109],"testing,":[110],"spectrometric":[111],"imaging,":[112],"feature":[113],"selection,":[114],"patter":[116],"recognition":[117],"utility":[121],"effectiveness":[123],"evaluated":[128],"terms":[130],"some":[132],"standard":[133],"performance":[134],"criteria":[135],"computational":[138],"complexity,":[139],"variance":[140],"distribution,":[141],"mean-square":[142],"error,":[143,146,152],"correlated":[144],"rms":[145],"rate":[147],"distortion,":[148],"data":[149],"compression,":[150],"classification":[151],"hardware":[155],"realization.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":19},{"year":2014,"cited_by_count":18},{"year":2013,"cited_by_count":25},{"year":2012,"cited_by_count":23}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}