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    On forward and inverse uncertainty quantification for models involving hysteresis operators
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2018) Klein, Olaf; Davino, Daniele; Visone, Ciro
    Parameters within hysteresis operators modeling real world objects have to be identified from measurements and are therefore subject to corresponding errors. To investigate the influence of these errors, the methods of Uncertainty Quantification (UQ) are applied.