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Classifying Weak Phase Retrieval by Casazza, P. G.; Akrami, F. is a scholarly article available to read on EtoBox.

What is Classifying Weak Phase Retrieval about?

We will give several surprising equivalences and consequences of weak phase retrieval. These results give a complete understanding of the difference between weak phase retrieval and phase retrieval. We also answer two longstanding open problems on weak phase retrieval: (1) We show that the families of weak phase retrievable frames $\{x_{i}\}_{i=1}^{m}$ in $\mathbb{R}^n$ are not dense in the family of $m$-element sets of vectors in $\mathbb{R}^n$ for all $m\ge 2n-2$; (2) We show that any frame $\{x_i\}_{i=1}^{2n-2}$ containing one or more canonical basis vectors in $\mathbb{R}^n$ cannot do weak phase retrieval. We provide numerous examples to show that the obtained results are best possible.

Author

Casazza, P. G.; Akrami, F.

Published

2023

Language

EN