Simple activation functions for neural and fuzzy neural networks
Boubekeur Mendil, K. Benmahammed · 2003
In this paper, we propose some activation functions designed to simplify the computational complexity and the hardware implementation of neural and fuzzy neural networks. These functions approximate the sigmoidal and the Gaussian shapes using only simple arithmetic operations. The simulation results show the good approximation capabilities of the resulting networks.