Oberseminar Wissenschaftliches Rechnen (Markus Pohlmann, Georg-August-Universität Göttingen)

Abstract:

We start this talk by giving a brief overview of the core ideas of testing and minimax distinguishability. Afterwards, we focus on linear inverse problems with Gaussian white noise. In this setting, we provide asymptotic upper and lower bounds for the minimax detection threshold of signals which are members of certain collections of frame vectors. The thresholds will be characterized in terms of the redundancy of the frame and the degree of ill-posedness of the inverse problem corresponding to the forward operator. We are especially interested in nding combinations of signals and operators for which sharp thresholds can be derived, which means that the upper and lower bounds coincide. Finally, we discuss our results for the example of the 2D Radon transform.

via Zoom video conference (request the Zoom link from frank.werner@mathematik.uni-wuerzburg.de)
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