Implementing nonlinear activation functions in neural network emulators

Abstract

An alternative approach to implementing nonlinear activation functions for digital neural networks is presented. Unlike other methods, this approach has the advantage that it is processed by a common arithmetic unit already required for the network computations and it does not require the use of a look-up table.