Neurodynamic Algorithms With Finite/Fixed-Time Convergence for Sparse Optimization via ℓ<sub>1</sub> Regularization-Reference-Cited by-同舟云学术

Neurodynamic Algorithms With Finite/Fixed-Time Convergence for Sparse Optimization via ℓ₁ Regularization

Published:2024-01 Issue:1 Volume:54 Page:131-142
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Wen Hongsong¹^ORCID,He Xing¹^ORCID,Huang Tingwen²^ORCID,Yu Junzhi³^ORCID

Affiliation:

1. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronics and Information Engineering, Southwest University, Chongqing, China

2. Department of Mathematics, Texas A&M University at Qatar, Doha, Qatar

3. Department of Advanced Manufacturing and Robotics, College of Engineering, State Key Laboratory for Turbulence and Complex Systems, Peking University, Beijing, China

Funder

Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221021/10364887/10235315.pdf?arnumber=10235315

Reference38 articles.

1. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

2. Non-local sparse models for image restoration