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.
|Number of pages||4|
|Publication status||Published - 1 Oct 2015|
|Event||2015 IEEE 13th International Conference on Industrial Informatics (INDIN) - |
Duration: 22 Jul 2015 → 24 Jul 2015
|Conference||2015 IEEE 13th International Conference on Industrial Informatics (INDIN)|
|Period||22/07/15 → 24/07/15|