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Issue No.09 - September (1996 vol.45)
pp: 1045-1049
<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.
Stamatis Vassiliadis, Ming Zhang, "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
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