Issue No.09 - September (1996 vol.45)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/12.537127
<p><b>Abstract</b>—A piecewise second order approximation scheme is proposed for computing the sigmoid function. The scheme provides high performance with low implementation cost; thus, it is suitable for hardwired cost effective neural emulators. It is shown that an implementation of the sigmoid generator outperforms, in both precision and speed, existing schemes using a bit serial pipelined implementation. The proposed generator requires one multiplication, no look-up table and no addition. It has been estimated that the sigmoid output is generated with a maximum computation delay of 21 bit serial machine cycles representing a speedup of 1.57 to 2.23 over other proposals.</p>
Nonlinear function generators, sigmoid function, piecewise approximations, neural networks, hardware for twos complement notation, error analysis.
Ming Zhang, Stamatis Vassiliadis, José G. Delgado-Frias, "Sigmoid Generators for Neural Computing Using Piecewise Approximations", IEEE Transactions on Computers, vol.45, no. 9, pp. 1045-1049, September 1996, doi:10.1109/12.537127