Applications of independent component analysis for nuclear physics data

The major dissertation objective is to apply artificial intelligence technologies to the analysis of physics data. Independent Component Analysis (ICA) is a new and generally applicable method for several theoretical and practical challenges, mainly in signal processing, but no previous application of ICA to problems in physics has been reported in the literature. The present work has identified promising opportunities for future exploration in this area. Results are obtained for some particular experimental data including applications that improve the analysis of angular distribution and excitation function data from nuclear reactions.