  Experiments aiming at high sensitivities usually demand for a very high
statistics in order to reach more precise measurements. However, for those
exploiting Low Temperature Detectors (LTDs), a high source activity may
represent a drawback, if the events rate becomes comparable with the detector
characteristic temporal response. Indeed, since commonly used optimum filtering
approaches can only process LTDs signals well isolated in time, a
non-negligible part of the recorded experimental data-set is discarded and
hence constitute the dead-time. In the presented study we demonstrate that,
thanks to the matrix optimum filtering approach, the dead-time of an experiment
exploiting LTDs can be strongly reduced.
