7th International Conference on Computational Harmonic Analysis Vanderbilt University Nashville, TN, USA May 14{18, 2018 Spatio-Temporal Trade-Off for Initial Data Best Approximation Roza Aceska Ball State University
[email protected] Coauthors: Alessandro Arsie and Ramesh Karki We present a mathematical framework and efficient computational schemes to solve some classes of PDEs from scarcely sampled initial data. Full knowledge of the initial conditions in an initial value problem (IVP) is essential but often impossible to attain; the way to overcome this impairing is to exploit the evo- lutionary nature of the problem at hand, while working with a reduced number of sensors. Our framework combines spatial samples of various temporal states of the system of interest, thus compensating for the lack of knowledge of the initial conditions. Stable phase retrieval in infinite dimensions Rima Alaifari ETH Zurich, Switzerland
[email protected] Coauthors: Ingrid Daubechies (Duke University), Philipp Grohs (University of Vienna), Rujie Yin (Duke University) Phase retrieval is the problem of reconstructing a signal from only the mag- nitudes of a set of complex measurements. The missing information of the phase of the measurements severely obstructs the signal reconstruction. While the problem is stable in the finite dimensional setting, it is very ill- conditioned. This makes it necessary to study the stability and regularization properties in an infinite-dimensional setting. We show that in some sense the ill- conditioning is independent of the redundancy of the measurements. However, the instabilities observed in practice are all of a certain type. Motivated by this observation, we introduce a new paradigm for stable phase retrieval.