Dec 27, 2018 · In this paper, this problem is tackled by minimizing the sum of a nonconvex least-squares fit criterion and a penalty term. We assume that the ...
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In this work, this problem is tackled by minimizing the sum of a non convex least-squares fit criterion and a penalty term. We assume that the nonlinearity of ...
Recovering nonlinearly degraded signal in the presence of noise is a challenging problem. In this work, this problem is tackled by minimizing the sum of a ...
This problem is tackled by minimizing the sum of a nonconvex least-squares fit criterion and a penalty term and it is proposed to use a sparse relaxation ...
In addition, we suppose that the signal to be sought is sparse and a rational approximation of the ℓ0 pseudo-norm thus constitutes a suitable penalization. The ...
How to Globally Solve Non-convex Optimization Problems Involving an Approximate ℓ 0 Penalization. Conference Paper. May 2019. Arthur Marmin · Marc Castella ...
In addition, we suppose that the signal to be sought is sparse and a rational approximation of the ℓ 0 pseudonorm thus constitutes a suitable penalization.
-C. Pesquet, and A. Marmin. Rational optimization for nonlinear reconstruction with approximate ℓ0 penalization. IEEE Transactions on Signal Processing, 67 ...
Apr 25, 2024 · Rational Optimization for Nonlinear Reconstruction With Approximate ℓ0 Penalization. IEEE Trans. Signal Process. 67(6): 1407-1417 (2019).
We propose a method to reconstruct sparse signals degraded by a nonlinear distortion and acquired at a limited sampling rate.