Communication Dans Un Congrès Année : 2025

Signal estimation from correlation vectors with structured low-rank approximation

Résumé

The paper focuses on the reconstruction of a multivariate signal from its noisy correlation vectors, a problem appearing in phase retrieval and blind channel identification. In the noiseless case, the signals can be retrieved from greatest common divisors of the polynomials associated to observed vectors. For the noisy case, by exploiting the properties of Sylvester matrices, we propose a new reconstruction approach that exploits all the available data and preserves matrix structure in the associated low-rank approximation problem. By doing so, we achieve an improvement of the reconstruction performance with respect to existing methods.

Fichier principal
Vignette du fichier
25eusipco_sylvester_slra_final.pdf (309.65 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-05122986 , version 1 (20-06-2025)

Licence

Identifiants

  • HAL Id : hal-05122986 , version 1

Citer

Antonio Fazzi, Julien Flamant, Konstantin Usevich. Signal estimation from correlation vectors with structured low-rank approximation. 33rd European Signal Processing Conference, EUSIPCO 2025, Sep 2025, Isola delle Femmine – Palermo, Italy. ⟨hal-05122986⟩
179 Consultations
247 Téléchargements

Partager

  • More