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Projected Wirtinger Gradient Descent for Digital Waves Reconstruction
Journal article   Open access   Peer reviewed

Projected Wirtinger Gradient Descent for Digital Waves Reconstruction

S H Liu, L L Shi and W Y Xu
TRAITEMENT DU SIGNAL, Vol.37(6), pp.919-927
2020
DOI: 10.18280/ts.370605
url
https://doi.org/10.18280/ts.370605View
Published (Version of record) Open Access

Abstract

This work attempts to recover digital signals from a few stochastic samples in time domain. The target signal is the linear combination of one-dimensional complex sine components with R different but continuous frequencies. These frequencies control the continuous values in the domain of normalized frequency [0, 1), contrary to the previous research into compressed sensing. To recover the target signal, the problem was transformed into the completion of a low-rank structured matrix, drawing on the linear property of the Hankel matrix. Based on the completion of the structured matrix, the authors put forward a feasible-point algorithm, analyzed its convergence, and speeded up the convergence with the fast iterative shrinkage-thresholding (FIST) algorithm. The initial algorithm and the speed up strategy were proved effective through repeated numerical simulations. The research results shed new lights on the signal recovery in various fields.

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