Local independent component analysis applied to highly segmented detectors

A novel particle discrimination strategy is proposed in this work for the ATLAS detector high-level trigger. The available data set, composed by electron and jet signatures, was clustered using self-organizing maps and local independent components were estimated for each group. A hybrid neural-genetic structure was used as classifier. Considered performance improvement was achieved with the proposed approach, 97.5% of electrons were correctly identified for 3 % jet misclassication.