Analysis of some Krylov subspace methods for normal matrices via approximation theory and convex optimization

Keyphrases

• Approximation Theory 100%
• Convex Optimization 100%
• Krylov Subspace Methods 100%
• Normal Matrix 100%
• Convergence Analysis 66%
• Finite Sets 33%
• Convergence Rate 33%
• Eigenvector 33%
• Maximization Problem 33%
• Krylov Subspace 33%
• Approximation Problem 33%
• Karush-Kuhn-Tucker Optimality Conditions 33%
• Krylov Sequence 33%
• Arnoldi Iteration 33%
• GMRES Method 33%
• Krylov Matrix 33%
• Convex Maximization 33%
• Min-max Approximation 33%
• Polynomial Space 33%
• Residual Norm 33%
• Constrained Convex Optimization 33%
• Naturally-derived 33%
• Column Vectors 33%
• Developing Tools 33%
• Best Approximation Polynomial 33%

Mathematics

• Approximation Theory 100%
• Matrix 100%
• Normal Matrix 100%
• Polynomial 66%
• Convergence Analysis 66%
• Upper Bound 66%
• Residuals 33%
• Best Approximation 33%
• Approximation Problem 33%
• Min-Max 33%
• Finite Set 33%
• Main Result 33%
• Column Vector 33%
• Eigenvector 33%
• Rate of Convergence 33%
• Optimality Condition 33%