Axel Flinth
About Axel Flinth
My research is dealing with theoretical aspects of mathematical signal processing, with focus on the application of optimization for signal reconstruction from linear measurements. A lot of my research operates within the field of “compressed sensing”, where assumptions about the structure of the signals are used for enabling, or enhancing, methods for reconstructing them. With the help of regularized optimization problems, and/or tailor-made algorithms, it is possible to reconstruct (extrinsically) n-dimensional objects from far fewer than n measurements.
My special interest is infinite-dimensional versions of the mentioned optimization problems. Especially appealing to me is that the field combines tools from many areas within mathematics: convex geometry, optimization, mathematical statistics and functional analysis.
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Reliable Recovery of Hierarchically Sparse Signals for Gaussian and Kronecker Product
Measurements
I. Roth, M. Kliesch, Axel Flinth, G. Wunder, J. Eisert
Ieee Transactions on Signal Processing - 2020-01-01 -
On the linear convergence rates of exchange and continuous methods for total variation
minimization
Axel Flinth, F. de Gournay, P. Weiss
Mathematical Programming - 2020-01-01