An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel Zone

In this article, we tackle the question of evaluating the dimension of the data space in the phase retrieval problem. With the aim to achieve this task, we first exploit the lifting technique to recast the quadratic model as a linear one. After that, we evaluate analytically the singular values of t...

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Main Authors: Rocco Pierri, Raffaele Moretta
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/10/5/606
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author Rocco Pierri
Raffaele Moretta
author_facet Rocco Pierri
Raffaele Moretta
author_sort Rocco Pierri
collection DOAJ
description In this article, we tackle the question of evaluating the dimension of the data space in the phase retrieval problem. With the aim to achieve this task, we first exploit the lifting technique to recast the quadratic model as a linear one. After that, we evaluate analytically the singular values of the lifting operator, and we quantify the dimension of the data space by counting the number of “significant” singular values. In the last part of the article, we show some numerical results in order to corroborate our analytical prediction on the singular values’ behavior of the lifting operator and on the dimension of the data space. The analysis is performed for a 2D scalar geometry consisting of an electric current strip whose square magnitude of the radiated field is observed on multiple arcs of circumference in Fresnel zone.
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spelling doaj.art-5765bf7504004634a10963e65d2d6b8b2023-12-03T12:39:53ZengMDPI AGElectronics2079-92922021-03-0110560610.3390/electronics10050606An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel ZoneRocco Pierri0Raffaele Moretta1Dipartimento di Ingegneria, Università della Campania “Luigi Vanvitelli”, Via Roma 29, 81031 Aversa, ItalyDipartimento di Ingegneria, Università della Campania “Luigi Vanvitelli”, Via Roma 29, 81031 Aversa, ItalyIn this article, we tackle the question of evaluating the dimension of the data space in the phase retrieval problem. With the aim to achieve this task, we first exploit the lifting technique to recast the quadratic model as a linear one. After that, we evaluate analytically the singular values of the lifting operator, and we quantify the dimension of the data space by counting the number of “significant” singular values. In the last part of the article, we show some numerical results in order to corroborate our analytical prediction on the singular values’ behavior of the lifting operator and on the dimension of the data space. The analysis is performed for a 2D scalar geometry consisting of an electric current strip whose square magnitude of the radiated field is observed on multiple arcs of circumference in Fresnel zone.https://www.mdpi.com/2079-9292/10/5/606phase retrievalnonlinear inversiondata space dimensionindependent data
spellingShingle Rocco Pierri
Raffaele Moretta
An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel Zone
Electronics
phase retrieval
nonlinear inversion
data space dimension
independent data
title An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel Zone
title_full An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel Zone
title_fullStr An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel Zone
title_full_unstemmed An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel Zone
title_short An SVD Approach for Estimating the Dimension of Phaseless Data on Multiple Arcs in Fresnel Zone
title_sort svd approach for estimating the dimension of phaseless data on multiple arcs in fresnel zone
topic phase retrieval
nonlinear inversion
data space dimension
independent data
url https://www.mdpi.com/2079-9292/10/5/606
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