## Abstract

The problem of recovering a pair of signals from their blind phaseless short-time Fourier transform measurements arises in several important phase retrieval applications, including ptychography and ultra-short pulse characterization. In this paper, we prove that in order to determine a pair of generic signals uniquely, up to trivial ambiguities, the number of phaseless measurements one needs to collect is, at most, five times the number of parameters required to describe the signals. This result improves significantly upon previous papers, which required the number of measurements to be quadratic in the number of parameters rather than linear. In addition, we consider the simpler problem of recovering a pair of generic signals from their blind short-time Fourier transform, when the phases are known. In this setting, which can be understood as a special case of the blind deconvolution problem, we show that the number of measurements required to determine the two signals, up to trivial ambiguities, equals exactly the number of parameters to be recovered. As a side result, we study the classical phase retrieval problem - that is, recovering a signal from its Fourier magnitudes - when some entries of the signal are known a priori. We derive a bound on the number of required measurements as a function of the size of the set of known entries. Specifically, we show that if most of the signal's entries are known, then only a few Fourier magnitudes are necessary to determine a signal uniquely.

Original language | English |
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Article number | 8866750 |

Pages (from-to) | 3232-3241 |

Number of pages | 10 |

Journal | IEEE Transactions on Information Theory |

Volume | 66 |

Issue number | 5 |

Early online date | 11 Oct 2019 |

DOIs | |

State | Published - May 2020 |

## Keywords

- FROG
- Phase retrieval
- blind deconvolution
- ptychography
- short-time Fourier transform
- ultra-short pulse characterization

## All Science Journal Classification (ASJC) codes

- Information Systems
- Computer Science Applications
- Library and Information Sciences