FPGA implementation of Feed-Forward Neural Networks for smart devices development

Abstract

This paper presents the results obtained in the implementation of Feed-Forward Artificial Neural Networks (FF-ANN) with one or several layers, used in the development of smart devices that needs learning capability and adaptive behavior. The networks were implemented using ANN specific blocks created by the authors using the System Generator software. The training and the testing of the networks was conducted using sets of 150 training and test vectors with 7 elements.