{"id":"https://openalex.org/W3133671857","doi":"https://doi.org/10.1109/tcsi.2021.3061321","title":"Reduced Complexity Optimal Convolution Based on the Discrete Hirschman Transform","display_name":"Reduced Complexity Optimal Convolution Based on the Discrete Hirschman Transform","publication_year":2021,"publication_date":"2021-03-02","ids":{"openalex":"https://openalex.org/W3133671857","doi":"https://doi.org/10.1109/tcsi.2021.3061321","mag":"3133671857"},"language":"en","primary_location":{"id":"doi:10.1109/tcsi.2021.3061321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2021.3061321","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-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/A5035887746","display_name":"Dingli Xue","orcid":"https://orcid.org/0000-0003-1633-7233"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dingli Xue","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0000-0003-1633-7233","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006876328","display_name":"Linda S. DeBrunner","orcid":"https://orcid.org/0000-0001-9926-8602"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linda S. DeBrunner","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0000-0001-9926-8602","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035366862","display_name":"Victor DeBrunner","orcid":"https://orcid.org/0000-0003-2198-2552"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Victor DeBrunner","raw_affiliation_strings":["Florida State University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0000-0003-2198-2552","affiliations":[{"raw_affiliation_string":"Florida State University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":0.5822,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.67198787,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"68","issue":"5","first_page":"2051","last_page":"2059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.9994999766349792,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.8309085369110107},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.708957314491272},{"id":"https://openalex.org/keywords/circular-convolution","display_name":"Circular convolution","score":0.6854637861251831},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6157494187355042},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.597460150718689},{"id":"https://openalex.org/keywords/convolution-theorem","display_name":"Convolution theorem","score":0.5909808874130249},{"id":"https://openalex.org/keywords/overlap\u2013add-method","display_name":"Overlap\u2013add method","score":0.5860458612442017},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5624163746833801},{"id":"https://openalex.org/keywords/discrete-fourier-transform","display_name":"Discrete Fourier transform (general)","score":0.5613247156143188},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5214099884033203},{"id":"https://openalex.org/keywords/discrete-hartley-transform","display_name":"Discrete Hartley transform","score":0.5082396864891052},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4795260429382324},{"id":"https://openalex.org/keywords/convolution-power","display_name":"Convolution power","score":0.4586266875267029},{"id":"https://openalex.org/keywords/raders-fft-algorithm","display_name":"Rader's FFT algorithm","score":0.44040510058403015},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.3256271481513977},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.32396507263183594},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.1433500349521637},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.11318987607955933},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.09079882502555847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08109331130981445},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.059923022985458374},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.05243745446205139}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.8309085369110107},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.708957314491272},{"id":"https://openalex.org/C194980680","wikidata":"https://www.wikidata.org/wiki/Q245450","display_name":"Circular convolution","level":5,"score":0.6854637861251831},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6157494187355042},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.597460150718689},{"id":"https://openalex.org/C79587385","wikidata":"https://www.wikidata.org/wiki/Q2638931","display_name":"Convolution theorem","level":5,"score":0.5909808874130249},{"id":"https://openalex.org/C181002996","wikidata":"https://www.wikidata.org/wiki/Q1611641","display_name":"Overlap\u2013add method","level":5,"score":0.5860458612442017},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5624163746833801},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.5613247156143188},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5214099884033203},{"id":"https://openalex.org/C192853989","wikidata":"https://www.wikidata.org/wiki/Q1006531","display_name":"Discrete Hartley transform","level":5,"score":0.5082396864891052},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4795260429382324},{"id":"https://openalex.org/C86254553","wikidata":"https://www.wikidata.org/wiki/Q5166605","display_name":"Convolution power","level":5,"score":0.4586266875267029},{"id":"https://openalex.org/C69598009","wikidata":"https://www.wikidata.org/wiki/Q7280126","display_name":"Rader's FFT algorithm","level":5,"score":0.44040510058403015},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.3256271481513977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.32396507263183594},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.1433500349521637},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.11318987607955933},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.09079882502555847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08109331130981445},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.059923022985458374},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.05243745446205139},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsi.2021.3061321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2021.3061321","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems I: Regular Papers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1566387478","https://openalex.org/W1987138902","https://openalex.org/W1987741783","https://openalex.org/W1997654368","https://openalex.org/W2031621001","https://openalex.org/W2054215882","https://openalex.org/W2064980790","https://openalex.org/W2082727461","https://openalex.org/W2096121910","https://openalex.org/W2099206970","https://openalex.org/W2106344525","https://openalex.org/W2107868713","https://openalex.org/W2124092400","https://openalex.org/W2140929831","https://openalex.org/W2142603808","https://openalex.org/W2317906089","https://openalex.org/W2320045903","https://openalex.org/W2543382323","https://openalex.org/W2756095346","https://openalex.org/W2798924194","https://openalex.org/W2799196297","https://openalex.org/W2807127337","https://openalex.org/W2918622534","https://openalex.org/W2982446276","https://openalex.org/W3013510513","https://openalex.org/W3100446018","https://openalex.org/W4254389654","https://openalex.org/W4296980820"],"related_works":["https://openalex.org/W2267589039","https://openalex.org/W4363675452","https://openalex.org/W2361284596","https://openalex.org/W4372260258","https://openalex.org/W2033203427","https://openalex.org/W2293685972","https://openalex.org/W1483140925","https://openalex.org/W2759540840","https://openalex.org/W2982446276","https://openalex.org/W2160855435"],"abstract_inverted_index":{"The":[0],"Discrete":[1,11],"Hirschman":[2],"Transform":[3,13],"(DHT)":[4],"is":[5],"more":[6],"computationally":[7],"attractive":[8],"than":[9],"the":[10,25,39,49,69,78,83,96,105,109,139,159,173],"Fourier":[12],"(DFT).":[14],"Based":[15],"on":[16,56],"its":[17,30,120],"derived":[18],"linear":[19],"convolution,":[20,80],"we":[21,59,81],"have":[22],"confirmed":[23],"that":[24,61,114,138],"DHT-based":[26,50,79,111,141],"convolution":[27,42,51,112,142],"filter":[28,43,163],"shows":[29],"superiority":[31],"in":[32,44,72,85,122],"reducing":[33],"computations":[34,87,146],"conditionally,":[35],"while":[36],"compared":[37],"with":[38,113,169],"conventional":[40],"DFT-based":[41],"our":[45],"previous":[46],"work.":[47],"Since":[48],"has":[52,125],"many":[53],"configurations":[54],"depending":[55],"parameter":[57],"choices,":[58],"conjecture":[60],"there":[62],"should":[63],"be":[64],"an":[65,90],"optimal":[66,97,110,140],"case":[67],"for":[68,77,166],"largest":[70],"reduction":[71,121],"computations.":[73,101],"In":[74],"this":[75],"paper,":[76],"express":[82],"requirement":[84],"real":[86,145],"and":[88,150,154,162],"propose":[89],"approach":[91],"of":[92,108,115],"how":[93],"to":[94,99,158,172],"determine":[95],"parameters":[98],"reduce":[100,144],"We":[102],"further":[103],"compare":[104],"computational":[106],"load":[107],"other":[116],"popular":[117],"convolutions.":[118],"Moreover,":[119],"clock":[123,155],"cycles":[124],"also":[126],"been":[127],"estimated":[128],"using":[129],"a":[130],"Digital":[131],"Signal":[132],"Processor":[133],"(DSP)":[134],"TMS320C5545.":[135],"Results":[136],"indicate":[137],"can":[143],"(multiplications":[147],"by":[148,152],"9.09%-50%":[149],"additions":[151],"1.12%-51.09%)":[153],"cycles,":[156],"according":[157],"input":[160],"length":[161],"size,":[164],"except":[165],"some":[167],"cases":[168],"identical":[170],"performance":[171],"radix-2":[174],"FFT-based":[175],"competitor.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
