{"id":"https://openalex.org/W3116115339","doi":"https://doi.org/10.23919/eusipco47968.2020.9287739","title":"Memory Requirement Reduction of Deep Neural Networks for Field Programmable Gate Arrays Using Low-Bit Quantization of Parameters","display_name":"Memory Requirement Reduction of Deep Neural Networks for Field Programmable Gate Arrays Using Low-Bit Quantization of Parameters","publication_year":2020,"publication_date":"2020-12-18","ids":{"openalex":"https://openalex.org/W3116115339","doi":"https://doi.org/10.23919/eusipco47968.2020.9287739","mag":"3116115339"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco47968.2020.9287739","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco47968.2020.9287739","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th European Signal Processing Conference (EUSIPCO)","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/A5079877432","display_name":"Niccol\u00f2 Nicodemo","orcid":"https://orcid.org/0000-0001-8322-4250"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Niccolo Nicodemo","raw_affiliation_strings":["University of Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"University of Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001429662","display_name":"Gaurav Naithani","orcid":"https://orcid.org/0000-0001-6622-6457"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Gaurav Naithani","raw_affiliation_strings":["Audio Research Group, Tampere University, Finland"],"affiliations":[{"raw_affiliation_string":"Audio Research Group, Tampere University, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108358814","display_name":"Konstantinos Drossos","orcid":null},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Konstantinos Drossos","raw_affiliation_strings":["Audio Research Group, Tampere University, Finland"],"affiliations":[{"raw_affiliation_string":"Audio Research Group, Tampere University, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049691461","display_name":"Tuomas Virtanen","orcid":"https://orcid.org/0000-0002-4604-9729"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Tuomas Virtanen","raw_affiliation_strings":["Audio Research Group, Tampere University, Finland"],"affiliations":[{"raw_affiliation_string":"Audio Research Group, Tampere University, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076824578","display_name":"Roberto Saletti","orcid":"https://orcid.org/0000-0001-9594-3535"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Roberto Saletti","raw_affiliation_strings":["University of Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"University of Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5079877432"],"corresponding_institution_ids":["https://openalex.org/I108290504"],"apc_list":null,"apc_paid":null,"fwci":0.7619,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72335274,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"466","last_page":"470"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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":0.9987000226974487,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.777076244354248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6558603048324585},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5578119158744812},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4557861387729645},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4469435214996338},{"id":"https://openalex.org/keywords/intelligibility","display_name":"Intelligibility (philosophy)","score":0.4127127528190613},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3937951922416687},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.39013293385505676},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.35568767786026},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.310972660779953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31055980920791626},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14850005507469177},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1350707709789276}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.777076244354248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6558603048324585},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5578119158744812},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4557861387729645},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4469435214996338},{"id":"https://openalex.org/C60048801","wikidata":"https://www.wikidata.org/wiki/Q1433889","display_name":"Intelligibility (philosophy)","level":2,"score":0.4127127528190613},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3937951922416687},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.39013293385505676},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.35568767786026},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.310972660779953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31055980920791626},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14850005507469177},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1350707709789276},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/eusipco47968.2020.9287739","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco47968.2020.9287739","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:arpi.unipi.it:11568/1077300","is_oa":false,"landing_page_url":"https://hdl.handle.net/11568/1077300","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2058641082","https://openalex.org/W2067295501","https://openalex.org/W2115452265","https://openalex.org/W2119144962","https://openalex.org/W2246760854","https://openalex.org/W2276486856","https://openalex.org/W2294370754","https://openalex.org/W2319920447","https://openalex.org/W2341860434","https://openalex.org/W2612864759","https://openalex.org/W2766839578","https://openalex.org/W2803368114","https://openalex.org/W2891405874","https://openalex.org/W2899771611","https://openalex.org/W2903100766","https://openalex.org/W2912168260","https://openalex.org/W2949833565","https://openalex.org/W2952218014","https://openalex.org/W2953974830","https://openalex.org/W2962761403","https://openalex.org/W2962824709","https://openalex.org/W2962866211","https://openalex.org/W2964121744","https://openalex.org/W2964299589","https://openalex.org/W2998218113","https://openalex.org/W3099330747","https://openalex.org/W3118447446","https://openalex.org/W3208082774","https://openalex.org/W3210141620","https://openalex.org/W6631190155","https://openalex.org/W6677580257","https://openalex.org/W6691194387","https://openalex.org/W6696126599","https://openalex.org/W6700264148","https://openalex.org/W6704098239","https://openalex.org/W6745499037","https://openalex.org/W6751609549","https://openalex.org/W6756040250","https://openalex.org/W6756705316","https://openalex.org/W6758625146","https://openalex.org/W6787907751"],"related_works":["https://openalex.org/W2373674497","https://openalex.org/W2081919107","https://openalex.org/W2768478174","https://openalex.org/W2010050186","https://openalex.org/W3204400881","https://openalex.org/W3214410901","https://openalex.org/W3204296682","https://openalex.org/W3183118997","https://openalex.org/W2917767146","https://openalex.org/W4285818394"],"abstract_inverted_index":{"Effective":[0],"employment":[1],"of":[2,50,53,108,117],"deep":[3],"neural":[4],"networks":[5],"(DNNs)":[6],"in":[7,61],"mobile":[8],"devices":[9],"and":[10,24,40,94],"embedded":[11],"systems,":[12],"like":[13],"field":[14],"programmable":[15],"gate":[16],"arrays,":[17],"is":[18,71,87,92,97],"hampered":[19],"by":[20,128],"requirements":[21],"for":[22],"memory":[23,90,120],"computational":[25],"power.":[26],"In":[27],"this":[28],"paper":[29],"we":[30],"propose":[31],"a":[32,36,41,62,67,114],"method":[33,60],"that":[34],"employs":[35],"non-uniform":[37],"fixed-point":[38],"quantization":[39,52,111],"virtual":[42],"bit":[43],"shift":[44],"(VBS)":[45],"to":[46,73,113],"improve":[47],"the":[48,51,54,75,80,100,109,118,123],"accuracy":[49],"DNN":[55,70,86,119],"weights.":[56],"We":[57],"evaluate":[58],"our":[59],"speech":[63,77,83],"enhancement":[64],"application,":[65],"where":[66],"fully":[68],"connected":[69],"used":[72],"predict":[74],"clean":[76],"spectrum":[78],"from":[79],"input":[81],"noisy":[82],"spectrum.":[84],"A":[85],"optimized,":[88],"its":[89,95],"requirement":[91,121],"calculated,":[93],"performance":[96,125],"evaluated":[98],"using":[99],"short-time":[101],"objective":[102],"intelligibility":[103],"(STOI)":[104],"metric.":[105],"The":[106],"application":[107],"low-bit":[110],"leads":[112],"50%":[115],"reduction":[116],"while":[122],"STOI":[124],"drops":[126],"only":[127],"2.7%.":[129]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
