Dictionary Learning with Statistical Sparsity in the Presence of Noise - Archive ouverte HAL Access content directly
Conference Papers Year :

Dictionary Learning with Statistical Sparsity in the Presence of Noise

(1) , (2, 3) , (1)
1
2
3

Abstract

We consider a new stochastic formulation of sparse representations that is based on the family of symmetric α-stable (SαS) distributions. Within this framework, we develop a novel dictionary-learning algorithm that involves a new estimation technique based on the empirical characteristic function. It finds the unknown parameters of an SαS law from a set of its noisy samples. We assess the robustness of our algorithm with numerical examples.
Fichier principal
Vignette du fichier
Aziznejad_Eusipco_2020.pdf (385.87 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Loading...

Dates and versions

hal-02966135 , version 1 (13-10-2020)

Identifiers

  • HAL Id : hal-02966135 , version 1

Cite

Shayan Aziznejad, Emmanuel Soubies, Michael Unser. Dictionary Learning with Statistical Sparsity in the Presence of Noise. 28th European Signal Processing Conference - EUSIPCO 2020, Jan 2021, Amsterdam, Netherlands. pp.2026-2029. ⟨hal-02966135⟩
75 View
139 Download

Share

Gmail Facebook Twitter LinkedIn More