The talk discusses non-stationary inverse problems: The goal
is to estimate a state of a time-varying object by indirect
observations when the object is changing during the data
acquisition. Such problams arise e.g. in biomedical applications
and industrial process monitoring. The problem is tackled by
using Bayesian filtering methods. The talk gives an introduction
to this topic and some applications are presented.