Fission chamber's neutron signal characterization using nonnegative matrix factorization

In this work, we apply Nonnegative Matrix Factorization (NMF) algorithms of the blind source separation methods to extract independent components from signals recorded at the output of fission chamber detector, which is used to perform the flux-mapping within the nuclear research reactors. The simulation of the recorded signals is based on using the python-based of Fission Chambers (pyFC) suite code, employs the TRIM code and the Bolzig software. The output signals of the simulated fission chamber will be processed through Nonnegative Matrix Factorization techniques in order to achieve blind source separation task. The selection of the most efficient NMF technique is carried out by computing the performance index of separability of each algorithm and the extracted independent components that will be characterized by using time-frequency representation.