{"id":"https://openalex.org/W4408281303","doi":"https://doi.org/10.1109/iecon55916.2024.10905146","title":"HLS design of a reconfigurable Quaternion Neural Network hardware accelerator","display_name":"HLS design of a reconfigurable Quaternion Neural Network hardware accelerator","publication_year":2024,"publication_date":"2024-11-03","ids":{"openalex":"https://openalex.org/W4408281303","doi":"https://doi.org/10.1109/iecon55916.2024.10905146"},"language":"en","primary_location":{"id":"doi:10.1109/iecon55916.2024.10905146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon55916.2024.10905146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society","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/A5060409875","display_name":"Alin Tisan","orcid":"https://orcid.org/0000-0002-8280-2722"},"institutions":[{"id":"https://openalex.org/I184558857","display_name":"Royal Holloway University of London","ror":"https://ror.org/04g2vpn86","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I184558857"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Alin Tisan","raw_affiliation_strings":["Royal Holloway, University of London,Electronic Engineering Department,UK"],"affiliations":[{"raw_affiliation_string":"Royal Holloway, University of London,Electronic Engineering Department,UK","institution_ids":["https://openalex.org/I184558857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103038097","display_name":"Clive Cheong Took","orcid":"https://orcid.org/0000-0002-1640-1381"},"institutions":[{"id":"https://openalex.org/I184558857","display_name":"Royal Holloway University of London","ror":"https://ror.org/04g2vpn86","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I184558857"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Clive Cheong Took","raw_affiliation_strings":["Royal Holloway, University of London,Electronic Engineering Department,UK"],"affiliations":[{"raw_affiliation_string":"Royal Holloway, University of London,Electronic Engineering Department,UK","institution_ids":["https://openalex.org/I184558857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060409875"],"corresponding_institution_ids":["https://openalex.org/I184558857"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25937954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9598000049591064,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9581000208854675,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/quaternion","display_name":"Quaternion","score":0.7000405788421631},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6209518313407898},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.49009430408477783},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46950459480285645},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.45020216703414917},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.41438060998916626},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.397892028093338},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.38352158665657043},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16446968913078308},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12092870473861694}],"concepts":[{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.7000405788421631},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6209518313407898},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.49009430408477783},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46950459480285645},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.45020216703414917},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.41438060998916626},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.397892028093338},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.38352158665657043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16446968913078308},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12092870473861694},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon55916.2024.10905146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon55916.2024.10905146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society","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":19,"referenced_works":["https://openalex.org/W2009889957","https://openalex.org/W2111139814","https://openalex.org/W2118369318","https://openalex.org/W2144472563","https://openalex.org/W2163133162","https://openalex.org/W2492889297","https://openalex.org/W2800690434","https://openalex.org/W2912130874","https://openalex.org/W2966878259","https://openalex.org/W2975468520","https://openalex.org/W3163462841","https://openalex.org/W4210600196","https://openalex.org/W4292794775","https://openalex.org/W4310972252","https://openalex.org/W4386323923","https://openalex.org/W4388838027","https://openalex.org/W4392903735","https://openalex.org/W4401870872","https://openalex.org/W6637910052"],"related_works":["https://openalex.org/W3127350447","https://openalex.org/W3108700312","https://openalex.org/W4225472102","https://openalex.org/W2382948573","https://openalex.org/W1967938402","https://openalex.org/W2386041993","https://openalex.org/W1608572506","https://openalex.org/W2518118925","https://openalex.org/W3159273459","https://openalex.org/W3152699334"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,11,94],"rapid":[4],"field-programmable":[5],"gate":[6],"array":[7],"(FPGA)":[8],"prototyping":[9],"of":[10,28,58,87,90],"general":[12],"quaternion":[13],"based":[14,82],"Artificial":[15],"Neural":[16],"Network":[17],"(qANN)":[18],"algorithm":[19],"is":[20],"investigated.":[21],"The":[22,69],"design":[23,70],"method":[24,71],"involves":[25],"the":[26,29,85],"description":[27,80],"qANN":[30],"behaviour":[31],"in":[32,56],"C":[33],"programming":[34],"language":[35],"and":[36,47,51,66],"its":[37],"hardware":[38,63,79],"implementation,":[39],"using":[40],"VITIS":[41],"High-Level":[42],"Synthesis":[43],"(HLS)":[44],"tool.":[45],"Simulations":[46],"FPGA":[48,88],"implementation":[49],"results":[50],"their":[52],"analysis":[53],"are":[54],"presented":[55],"terms":[57],"performance":[59],"(data":[60],"accuracy)":[61],"vs":[62],"resources":[64],"used,":[65],"data":[67],"throughput.":[68],"proves":[72],"to":[73,78,93],"be":[74],"an":[75],"attractive":[76],"alternative":[77],"languages":[81],"design,":[83],"opening":[84],"field":[86],"acceleration":[89],"complex":[91],"algorithms":[92],"larger":[95],"audience.":[96]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
