The modified PRP conjugate gradient algorithm under a non-descent line search and its application in the Muskingum model and image restoration problems

DOI10.1007/s00500-021-05580-0zbMath1498.90176OpenAlexW3122777081WikidataQ113107571 ScholiaQ113107571MaRDI QIDQ2099954

Junyu Lu, Zhan Wang, Gong Lin Yuan

Publication date: 21 November 2022

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-021-05580-0

zbMATH Keywords

PRP methodstrongly global convergenceR-linear convergencenon-descent line search

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (8)

Two sufficient descent three-term conjugate gradient methods for unconstrained optimization problems with applications in compressive sensing ⋮ Adaptive three-term PRP algorithms without gradient Lipschitz continuity condition for nonconvex functions ⋮ Two diagonal conjugate gradient like methods for unconstrained optimization ⋮ Modified globally convergent Polak-Ribière-Polyak conjugate gradient methods with self-correcting property for large-scale unconstrained optimization ⋮ A hybrid conjugate gradient algorithm for nonconvex functions and its applications in image restoration problems ⋮ A hybrid HS-LS conjugate gradient algorithm for unconstrained optimization with applications in motion control and image recovery ⋮ An efficient modified AZPRP conjugate gradient method for large-scale unconstrained optimization problem ⋮ Globally convergent diagonal Polak-Ribière-Polyak like algorithm for nonlinear equations

Cites Work

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• Convergence analysis of a modified BFGS method on convex minimizations
• Generalized Polak-Ribière algorithm
• A globally convergent version of the Polak-Ribière conjugate gradient method
• Conjugate gradient methods with Armijo-type line searches.
• A class of parameter estimation methods for nonlinear Muskingum model using hybrid invasive weed optimization algorithm
• A conjugate gradient algorithm for large-scale nonlinear equations and image restoration problems
• Global convergence of BFGS and PRP methods under a modified weak Wolfe-Powell line search
• The PRP conjugate gradient algorithm with a modified WWP line search and its application in the image restoration problems
• Convergence Properties of Algorithms for Nonlinear Optimization
• Global Convergence Properties of Conjugate Gradient Methods for Optimization
• Conjugate Gradient Methods with Inexact Searches
• Rate of Convergence of Several Conjugate Gradient Algorithms
• A Characterization of Superlinear Convergence and Its Application to Quasi-Newton Methods
• A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
• Function minimization by conjugate gradients
• A Two-Term PRP-Based Descent Method
• The conjugate gradient method in extremal problems
• On the convergence properties of the unmodified PRP method with a non-descent line search
• Methods of conjugate gradients for solving linear systems
• A spectral conjugate gradient method for unconstrained optimization
• New properties of a nonlinear conjugate gradient method
• Benchmarking optimization software with performance profiles.

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