File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1016/j.laa.2014.02.011
- Scopus: eid_2-s2.0-84896541954
- Find via

Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Article: Phase retrieval from very few measurements
| Title | Phase retrieval from very few measurements |
|---|---|
| Authors | |
| Keywords | Computational complexity Informationally complete Phase retrieval Unit norm tight frames |
| Issue Date | 2014 |
| Citation | Linear Algebra and Its Applications, 2014, v. 449, p. 475-499 How to Cite? |
| Abstract | In many applications, signals are measured according to a linear process, but the phases of these measurements are often unreliable or not available. To reconstruct the signal, one must perform a process known as phase retrieval. This paper focuses on completely determining signals with as few intensity measurements as possible, and on efficient phase retrieval algorithms from such measurements. For the case of complex M-dimensional signals, we construct a measurement ensemble of size 4M-4 which yields injective intensity measurements; this is conjectured to be the smallest such ensemble. For the case of real signals, we devise a theory of "almost" injective intensity measurements, and we characterize such ensembles. Later, we show that phase retrieval from M+1 almost injective intensity measurements is NP-hard, indicating that computationally efficient phase retrieval must come at the price of measurement redundancy. © Published by Elsevier Inc. |
| Persistent Identifier | http://hdl.handle.net/10722/363721 |
| ISSN | 2023 Impact Factor: 1.0 2023 SCImago Journal Rankings: 0.837 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Fickus, Matthew | - |
| dc.contributor.author | Mixon, Dustin G. | - |
| dc.contributor.author | Nelson, Aaron A. | - |
| dc.contributor.author | Wang, Yang | - |
| dc.date.accessioned | 2025-10-10T07:48:55Z | - |
| dc.date.available | 2025-10-10T07:48:55Z | - |
| dc.date.issued | 2014 | - |
| dc.identifier.citation | Linear Algebra and Its Applications, 2014, v. 449, p. 475-499 | - |
| dc.identifier.issn | 0024-3795 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/363721 | - |
| dc.description.abstract | In many applications, signals are measured according to a linear process, but the phases of these measurements are often unreliable or not available. To reconstruct the signal, one must perform a process known as phase retrieval. This paper focuses on completely determining signals with as few intensity measurements as possible, and on efficient phase retrieval algorithms from such measurements. For the case of complex M-dimensional signals, we construct a measurement ensemble of size 4M-4 which yields injective intensity measurements; this is conjectured to be the smallest such ensemble. For the case of real signals, we devise a theory of "almost" injective intensity measurements, and we characterize such ensembles. Later, we show that phase retrieval from M+1 almost injective intensity measurements is NP-hard, indicating that computationally efficient phase retrieval must come at the price of measurement redundancy. © Published by Elsevier Inc. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Linear Algebra and Its Applications | - |
| dc.subject | Computational complexity | - |
| dc.subject | Informationally complete | - |
| dc.subject | Phase retrieval | - |
| dc.subject | Unit norm tight frames | - |
| dc.title | Phase retrieval from very few measurements | - |
| dc.type | Article | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1016/j.laa.2014.02.011 | - |
| dc.identifier.scopus | eid_2-s2.0-84896541954 | - |
| dc.identifier.volume | 449 | - |
| dc.identifier.spage | 475 | - |
| dc.identifier.epage | 499 | - |
