Publication:

A Methodology to Design Quantized Deep Neural Networks for Automatic Modulation Recognition

Date

2022
Journal article
https://doi.org/10.3390/a15120441
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dc.contributor.authorGoez, David
dc.contributor.authorSoto Arenas, Paola
dc.contributor.authorLatre, Steven
dc.contributor.authorGaviria, Natalia
dc.contributor.authorCamelo Botero, Miguel
dc.contributor.imecauthorGoez, David
dc.contributor.imecauthorSoto Arenas, Paola
dc.contributor.imecauthorLatre, Steven
dc.contributor.imecauthorCamelo Botero, Miguel
dc.contributor.orcidimecGoez, David::0000-0001-7658-0994
dc.contributor.orcidimecSoto Arenas, Paola::0000-0001-5906-6424
dc.contributor.orcidimecLatre, Steven::0000-0003-0351-1714
dc.contributor.orcidimecCamelo Botero, Miguel::0000-0001-8152-7143
dc.date.accessioned2023-03-02T13:49:31Z
dc.date.available2023-01-19T03:17:22Z
dc.date.available2023-03-02T13:49:31Z
dc.date.embargo2022-11-22
dc.date.issued2022
dc.description.wosFundingTextThis research was partially funded by the European Union's Horizon 2020 research and innovation program under Grant Agreement No. 101017109 (DAEMON), and by the Colombian Ministry of Science Technology and Innovation (Minciencias) and the Communications Regulation Commission (CRC), under the contract CT 80740-035-2022.
dc.identifier.doi10.3390/a15120441
dc.identifier.issn1999-4893
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/40994
dc.publisherMDPI
dc.source.beginpage441
dc.source.endpagena
dc.source.issue12
dc.source.journalALGORITHMS
dc.source.numberofpages21
dc.source.volume15
dc.subject.keywordsCLASSIFICATION
dc.title

A Methodology to Design Quantized Deep Neural Networks for Automatic Modulation Recognition

dc.typeJournal article
dspace.entity.typePublication
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