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[Joint work with Gero Friesecke] We consider phase retrieval on the space of square integrable functions. Assuming object space knowledge of the image (such as positivity or support), we show that the Error-Reduction algorithm may be viewed as a discretized gradient flow (without the need to explicitly impose object space constraints). We use this setting to analyze stagnation properties of the Error-Reduction algorithm and propose a novel Error-Reduction variant that outperforms standard algorithms.
This presentation is part of Contributed Presentation “CP8 - Contributed session 8”