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Neural Computing and Applications

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01.08.2013 | Original Article

A new solution to the hyperbolic tangent implementation in hardware: polynomial modeling of the fractional exponential part

verfasst von: Ivo Nascimento, Ricardo Jardim, Fernando Morgado-Dias

Erschienen in: Neural Computing and Applications | Ausgabe 2/2013

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Abstract

The most difficult part of an artificial neural network to implement in hardware is the nonlinear activation function. For most implementations, the function used is the hyperbolic tangent. This function has received much attention in relation to hardware implementation. Nevertheless, there is no consensus regarding the best solution. In this paper, we propose a new approach by implementing the hyperbolic tangent in hardware with a polynomial modeling of the fractional exponential part. The results in the paper then demonstrate, through the use of an example, that this solution is faster than the CORDIC algorithm, but slower than the piecewise linear solution with the same error. The advantage over the piecewise linear approach is that it uses less memory.

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Titel: A new solution to the hyperbolic tangent implementation in hardware: polynomial modeling of the fractional exponential part
verfasst von: Ivo Nascimento
Ricardo Jardim
Fernando Morgado-Dias
Publikationsdatum: 01.08.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 2/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-0919-0

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