Feature Selection and Neural Network for analysis of microstructural changes in magnetic materials

This work presents a Feature Selection Algorithm for optimization of a Probabilistic Neural Network. The aim of this Probabilistic Neural Network is classifying signals obtained from magnetic material samples where two micro-structural parameters were changed simultaneously. The combination of the Feature Selection Algorithm with the Probabilistic Neural Network shows both, classification rate outcomes and classification speed, higher than those coming from traditional Probabilistic Neural Networks.