An adaptive family of projection methods for constrained monotone nonlinear equations with applications

DOI10.1016/j.amc.2019.03.064zbMath1429.65107OpenAlexW2944005514MaRDI QIDQ2279399

Yang Liu, Chuanjiang He, Peiting Gao

Publication date: 12 December 2019

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2019.03.064

zbMATH Keywords

conjugate gradient methodprojection methodcompressed sensingmonotone equationsself-scaling memoryless BFGS update

Mathematics Subject Classification ID

Numerical computation of solutions to systems of equations (65H10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Methods of reduced gradient type (90C52)

Related Items (13)

A hybrid approach for finding approximate solutions to constrained nonlinear monotone operator equations with applications ⋮ An efficient projection-based algorithm without Lipschitz continuity for large-scale nonlinear pseudo-monotone equations ⋮ A family of inertial derivative-free projection methods for constrained nonlinear pseudo-monotone equations with applications ⋮ An inertial spectral CG projection method based on the memoryless BFGS update ⋮ A self-adaptive projection method for nonlinear monotone equations with convex constraints ⋮ Global convergence via modified self-adaptive approach for solving constrained monotone nonlinear equations with application to signal recovery problems ⋮ A new conjugate gradient projection method for convex constrained nonlinear equations ⋮ A modified inertial three-term conjugate gradient projection method for constrained nonlinear equations with applications in compressed sensing ⋮ PRP-like algorithm for monotone operator equations ⋮ A derivative-free \textit{RMIL} conjugate gradient projection method for convex constrained nonlinear monotone equations with applications in compressive sensing ⋮ A hybrid three-term conjugate gradient projection method for constrained nonlinear monotone equations with applications ⋮ A Perry-type derivative-free algorithm for solving nonlinear system of equations and minimizing ℓ₁regularized problem ⋮ An efficient conjugate gradient-based algorithm for unconstrained optimization and its projection extension to large-scale constrained nonlinear equations with applications in signal recovery and image denoising problems

Uses Software

• ACGSSV

Cites Work

• A self-adaptive three-term conjugate gradient method for monotone nonlinear equations with convex constraints
• Non-smooth equations based method for \(\ell_1\)-norm problems with applications to compressed sensing
• A modified Perry's conjugate gradient method-based derivative-free method for solving large-scale nonlinear monotone equations
• An adaptive three-term conjugate gradient method based on self-scaling memoryless BFGS matrix
• A projection method for convex constrained monotone nonlinear equations with applications
• A conjugate gradient method to solve convex constrained monotone equations with applications in compressive sensing
• A self-adjusting conjugate gradient method with sufficient descent condition and conjugacy condition
• Accelerated adaptive Perry conjugate gradient algorithms based on the self-scaling memoryless BFGS update
• Optimal conditioning of self-scaling variable Metric algorithms
• A Globally and Superlinearly Convergent Gauss--Newton-Based BFGS Method for Symmetric Nonlinear Equations
• Inexact Newton methods for the nonlinear complementarity problem
• Stable signal recovery from incomplete and inaccurate measurements
• Compressed sensing
• Benchmarking optimization software with performance profiles.

This page was built for publication: An adaptive family of projection methods for constrained monotone nonlinear equations with applications