Abstract

[David L. Elliott]

			      ABSTRACT

      A BETTER ACTIVATION FUNCTION FOR ARTIFICIAL NEURAL NETWORKS

    TR 93-8, Institute for Systems Research, University of Maryland

  by David L. Elliott--  ISR, NeuroDyne, Inc., and Washington University
                          January 29, 1993
The activation function  s(x) = x/(1 + |x|) is proposed for use in
digital simulation of neural networks, on the grounds that the 
computational operation count for this function is much smaller than
for those using exponentials and that it satisfies the simple differential
equation  s' = (1 + |s|)^2,  which generalizes the logistic equation.
The full report, a work-in-progress, is available in LaTeX or PostScript
form (two pages + titlepage) by request to delliott at src.umd.edu.