Implementation issues of sigmoid function and its derivative for VLSI digital neural networks

Abstract

This paper proposes a number of different implementations for the first derivative of the sigmoid function. The implementation of the sigmoid function employs a powers-of-two piecewise linear approximation. The best implementation scheme for the derivative is suggested based on overall speed performance (circuit speed and training time) and hardware requirements.