An end user platform for implementing artificial neutron networks on FPGA

The paper presents a novel neural design methodology based on the End User Programming concept. The proposed solution empowers end users, by means of abstracting the low-level hardware functionalities, to hardware implement Artificial Neural Networks (ANN) using field-programmable gate arrays (FPGA). The main outcomes include rapid ANN design and hardware implementation. A case study of an ANN as a pattern recognition module of an artificial olfaction system trained to identify four coffee brands is presented. An extended analysis has been carried out regarding the recognition rates versus training data features and data representation.