An augmented Lagrangian dual optimization approach to the \(H\)-weighted model updating problem
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Publication:396261
DOI10.1016/j.cam.2014.02.027zbMath1293.65054OpenAlexW2026678257MaRDI QIDQ396261
Publication date: 8 August 2014
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cam.2014.02.027
augmented Lagrangian dual methodinverse quadratic eigenvalue problemmodel updating problempartial eigendata
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Semidefinite programming (90C22) Eigenvalues, singular values, and eigenvectors (15A18) Inverse problems in linear algebra (15A29) Numerical solution of nonlinear eigenvalue and eigenvector problems (65H17)
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- Computing the nearest correlation matrix--a problem from finance
- Solving semidefinite-quadratic-linear programs using SDPT3
- Model-updating for self-adjoint quadratic eigenvalue problems
- Semi-definite programming techniques for structured quadratic inverse eigenvalue problems
- Finite element model updating in structural dynamics
- Semismoothness of solutions to generalized equations and the Moreau-Yosida regularization
- The Quadratic Eigenvalue Problem
- An augmented Lagrangian dual approach for the H-weighted nearest correlation matrix problem
- Semidefinite optimization
- A Dual Optimization Approach to Inverse Quadratic Eigenvalue Problems with Partial Eigenstructure
- Local structure of feasible sets in nonlinear programming, part II: Nondegeneracy
- Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
- Model Updating In Structural Dynamics: A Survey
- The Strong Second-Order Sufficient Condition and Constraint Nondegeneracy in Nonlinear Semidefinite Programming and Their Implications
- On the basic theorem of complementarity
- Constraint Nondegeneracy in Variational Analysis