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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/76564
Title: 
Approximation of hyperbolic tangent activation function using hybrid methods
Author(s): 
Institution: 
  • Universidade do Estado de Mato Grosso (UNEMAT)
  • Universidade Estadual Paulista (UNESP)
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.
Issue Date: 
16-Sep-2013
Citation: 
2013 8th International Workshop on Reconfigurable and Communication-Centric Systems-on-Chip, ReCoSoC 2013.
Keywords: 
  • activation function
  • FPGA
  • Hybrid Methods
  • hyperbolic tangent
  • Activation functions
  • Hybrid method
  • Hyperbolic tangent
  • Nonlinear activation functions
  • Nonlinear functions
  • Nonlinear problems
  • Reconfigurable devices
  • System architectures
  • Communication
  • Field programmable gate arrays (FPGA)
  • Hyperbolic functions
  • Neural networks
  • Reconfigurable hardware
Source: 
http://dx.doi.org/10.1109/ReCoSoC.2013.6581545
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/76564
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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