Second-order dynamical system for solving $\ell _{1}-\ell _{2}$ minimization problem and its applications

\(\ell _{1}-\ell _{2}\) minimization problem finds extensive applications across various domains, including signal processing, face recognition, and image restoration. This study begins by reformulating \(\ell _{1}-\ell _{2}\) minimization model into an equivalent fixed-point formulation via a projection-based residual method. Based on this, a new second-order continuous-time projection (2-CTP) algorithm is constructed by leveraging the theory of second-order dynamical systems. Subsequently, the existence and uniqueness of the solution to the proposed algorithm are established, and the convergence of its trajectories is further analyzed. To illustrate the effectiveness and performance of the developed method, numerical simulations covering applications in signal processing and image restoration are provided in the end.

Authors

Institutions

Publication Details

Journal
Journal of Inequalities and Applications
Published
2026-06-08
DOI
https://doi.org/10.1186/s13660-026-03496-7
Primary Topic
Sparse and Compressive Sensing Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Second-order dynamical system for solving $\ell _{1}-\ell _{2}$ minimization problem and its applications

Haitao Che, Han Yu
Journal of Inequalities and Applications
Sparse and Compressive Sensing Techniques
article

Second-order dynamical system for solving $\ell _{1}-\ell _{2}$ minimization problem and its applications

Haitao Che, Han Yu
article en

Abstract

\(\ell _{1}-\ell _{2}\) minimization problem finds extensive applications across various domains, including signal processing, face recognition, and image restoration. This study begins by reformulating \(\ell _{1}-\ell _{2}\) minimization model into an equivalent fixed-point formulation via a projection-based residual method. Based on this, a new second-order continuous-time projection (2-CTP) algorithm is constructed by leveraging the theory of second-order dynamical systems. Subsequently, the existence and uniqueness of the solution to the proposed algorithm are established, and the convergence of its trajectories is further analyzed. To illustrate the effectiveness and performance of the developed method, numerical simulations covering applications in signal processing and image restoration are provided in the end.

Journal of Inequalities and Applications
Qufu Normal University (CN), Weifang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province
Sustainable cities and communities
Openalex Percentile: Top 6%
Sparse and Compressive Sensing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Second-order dynamical system for solving $\ell _{1}-\ell _{2}$ minimization problem and its applications — Haitao Che, Han Yu · Journal of Inequalities and Applications (2026) | TGRS Research Map | TGRS