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simultaneous source separation

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Deep S$^3$PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models

Metzler, Christopher A., Wetzstein, Gordon

arXiv.org Machine LearningFeb-13-2020

This paper introduces and solves the simultaneous source separation and phase retrieval (S$^3$PR) problem. S$^3$PR shows up in a number application domains, most notably computational optics, where one has multiple independent coherent sources whose phase is difficult to measure. In general, S$^3$PR is highly under-determined, non-convex, and difficult to solve. In this work, we demonstrate that by restricting the solutions to lie in the range of a deep generative model, we can constrain the search space sufficiently to solve S$^3$PR.

algorithm, simultaneous source separation, source separation, (12 more...)

arXiv.org Machine Learning

2002.05856

Country:

North America > United States > California > Santa Clara County > Palo Alto (0.04)
Asia > Japan > Honshū > Chūbu > Toyama Prefecture > Toyama (0.04)

Genre: Research Report (0.50)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning > Generative AI (0.62)

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