Approximation of hyperbolic tangent activation function using hybrid methods

• Main Author: Sartin, Maicon A.
• Publication Date: 2013
• Other Authors: Da Silva, Alexandre C.R. [UNESP]
• Format: Conference object
• Language: eng
• Source: Repositório Institucional da UNESP
• Download full: http://dx.doi.org/10.1109/ReCoSoC.2013.6581545; http://hdl.handle.net/11449/76564
• topic: 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

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.