Abstract
Efficient design of sigmoid function for neural networks based FPGA is presented. Employing the hybrid CORDIC algorithm, the sigmoid function is described with VHDL in register transfer level. In order to enhance the efficiency and accuracy of implementation on Altera’s FPGA, the technology of pipeline and look-up table have been utilized. Through comparing the results obtained by the post-simulation of EDA tools with the results directly accounted by Matlab, it can be concluded that the designed model works accurately and efficiently.
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© 2006 Springer-Verlag Berlin Heidelberg
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Chen, X., Wang, G., Zhou, W., Chang, S., Sun, S. (2006). Efficient Sigmoid Function for Neural Networks Based FPGA Design. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_80
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DOI: https://doi.org/10.1007/11816157_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
Online ISBN: 978-3-540-37273-8
eBook Packages: Computer ScienceComputer Science (R0)