Sparse Regularization With Reverse Sorted Sum of Squares via an Unrolled Difference-of-Convex Approach
This paper proposes a sparse regularization method with a novel sorted regularization function. Sparse regularization is commonly used to solve underdetermined inverse problems. Traditional sparse regularization functions, such as <inline-formula><tex-math notation="LaTeX">$L_{...
Saved in:
Main Authors: | Takayuki Sasaki, Kazuya Hayase, Masaki Kitahara, Shunsuke Ono |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Open Journal of Signal Processing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10840312/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sparse View CT Reconstruction Algorithm Based on Non-Local Generalized Total Variation Regularization
by: Min JIANG, et al.
Published: (2025-01-01) -
Radius problems for a subclass of close-to-convex univalent functions
by: Khalida Inayat Noor
Published: (1992-01-01) -
Inertial-relaxed splitting for composite monotone inclusions
by: Oré, Ernesto, et al.
Published: (2023-02-01) -
A Joint Sparse Space-Time Adaptive Processing Method
by: Jinfeng Hu, et al.
Published: (2025-01-01) -
A modified proximal point algorithm for solving variational inclusion problem in real Hilbert spaces
by: Thierno M. M. Sow
Published: (2020-06-01)