FPGA realization of activation function for neural network

Abstract

This paper presents the FPGA implementation of neuron block units based on a sigmoid activation function for artificial neural networks (ANNs) applications. The proposed system was simulated using Modelsim XE II and synthesized using Synopsys design compiler based on TSMC 90 nm technology file. The functionality of backward propagation was successfully verified as compared with the python simulation results.