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DC Field | Value | Language |
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dc.contributor.author | Sartin, Maicon A. | - |
dc.contributor.author | Da Silva, Alexandre C.R. | - |
dc.date.accessioned | 2014-05-27T11:30:41Z | - |
dc.date.accessioned | 2016-10-25T18:54:09Z | - |
dc.date.available | 2014-05-27T11:30:41Z | - |
dc.date.available | 2016-10-25T18:54:09Z | - |
dc.date.issued | 2013-09-16 | - |
dc.identifier | http://dx.doi.org/10.1109/ReCoSoC.2013.6581545 | - |
dc.identifier.citation | 2013 8th International Workshop on Reconfigurable and Communication-Centric Systems-on-Chip, ReCoSoC 2013. | - |
dc.identifier.uri | http://hdl.handle.net/11449/76564 | - |
dc.identifier.uri | http://acervodigital.unesp.br/handle/11449/76564 | - |
dc.description.abstract | Artificial Neural Networks are widely used in various applications in engineering, as such solutions of nonlinear problems. The implementation of this technique in reconfigurable devices is a great challenge to researchers by several factors, such as floating point precision, nonlinear activation function, performance and area used in FPGA. The contribution of this work is the approximation of a nonlinear function used in ANN, the popular hyperbolic tangent activation function. The system architecture is composed of several scenarios that provide a tradeoff of performance, precision and area used in FPGA. The results are compared in different scenarios and with current literature on error analysis, area and system performance. © 2013 IEEE. | en |
dc.language.iso | eng | - |
dc.source | Scopus | - |
dc.subject | activation function | - |
dc.subject | FPGA | - |
dc.subject | Hybrid Methods | - |
dc.subject | hyperbolic tangent | - |
dc.subject | Activation functions | - |
dc.subject | Hybrid method | - |
dc.subject | Hyperbolic tangent | - |
dc.subject | Nonlinear activation functions | - |
dc.subject | Nonlinear functions | - |
dc.subject | Nonlinear problems | - |
dc.subject | Reconfigurable devices | - |
dc.subject | System architectures | - |
dc.subject | Communication | - |
dc.subject | Field programmable gate arrays (FPGA) | - |
dc.subject | Hyperbolic functions | - |
dc.subject | Neural networks | - |
dc.subject | Reconfigurable hardware | - |
dc.title | Approximation of hyperbolic tangent activation function using hybrid methods | en |
dc.type | outro | - |
dc.contributor.institution | Universidade do Estado de Mato Grosso (UNEMAT) | - |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | - |
dc.description.affiliation | Department of Computing UNEMAT - Universidade Do Estado de Mato Grosso, Colider, MT | - |
dc.description.affiliation | Department of Electrical Engineering UNESP - Universidade Estadual Paulista, Ilha Solteira, SP | - |
dc.description.affiliationUnesp | Department of Electrical Engineering UNESP - Universidade Estadual Paulista, Ilha Solteira, SP | - |
dc.identifier.doi | 10.1109/ReCoSoC.2013.6581545 | - |
dc.rights.accessRights | Acesso restrito | - |
dc.relation.ispartof | 2013 8th International Workshop on Reconfigurable and Communication-Centric Systems-on-Chip, ReCoSoC 2013 | - |
dc.identifier.scopus | 2-s2.0-84883659156 | - |
Appears in Collections: | Artigos, TCCs, Teses e Dissertações da Unesp |
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