A family of optimal weighted conjugate-gradient-type methods for strictly convex quadratic minimization

Keyphrases

• Convex Combination 100%
• Strictly Convex 100%
• Gradient Method 100%
• Merit Function 100%
• Quadratic Minimization Problem 100%
• Conjugate Gradient 100%
• Real Application 50%
• Eigenvalues 50%
• Numerical Solution 50%
• Numerical Results 50%
• Unique Solution 50%
• Value Function 50%
• Hessian 50%
• Convergence Behavior 50%
• Preconditioning Strategy 50%
• Unconstrained Optimization 50%
• Conjugate Gradient Method 50%
• Linear Convergence 50%
• Convex Quadratic Function 50%
• Fast Convergence 50%
• Weighted Gradient Method 50%
• Finite Termination 50%
• Linear Conjugate 50%
• Global Minimizer 50%
• Stationarity 50%
• Gradient Norm 50%
• Quadratic Function 50%
• Minimization Model 50%
• Value Reduction 50%

Mathematics

• Convex Combination 100%
• Strictly Convex 100%
• Quadratic Function 100%
• Type Method 100%
• Optimality 50%
• Numerical Solution 50%
• unique solution φ 50%
• Function Value 50%
• Eigenvalue 50%
• Objective Function 50%
• Linear Convergence 50%
• Conjugate Gradient Method 50%
• Convergence Behavior 50%
• Unconstrained Optimization Problem 50%
• Stationarity 50%
• Global Minimizer 50%

INIS

• convergence 100%
• minimization 100%
• applications 50%
• values 50%
• solutions 50%
• norm 50%
• reduction 50%
• optimization 50%
• eigenvalues 50%
• numerical solution 50%