Inverse Problems and Signal Processing in Industrial Applications
R. Ramlau (Johann Radon Institute for Computational and Applied Mathematics, Linz, Austria) and G. Teschke (University of Applied Sciences Neubrandenburg, Germany)
Many industrial applications require the extraction of information from indirect measurements. Usually, one faces two problems: First, one needs to model the connection between the observed data and the searched for information, and secondly the extraction /reconstruction has to be done in a stable way. Often the extraction process turns out to be ill - posed, and methods from regularization theory have to be employed in order to control the influence of the data noise in the extraction /reconstruction process. We plan to present different industrial applications for methods from signal processing and inverse problems, including examples from life sciences, optics, rotational dynamics, automotive industries and problems related to the atmosphere (e.g. weather forecasting).