A smoothing Newton-type method for solving the \(L _{2}\) spectral estimation problem with lower and upper bounds
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Publication:763390
DOI10.1007/s10589-010-9356-0zbMath1261.90056OpenAlexW1982301287MaRDI QIDQ763390
Guanglu Zhou, Chen Ling, Hong-Xia Yin
Publication date: 9 March 2012
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10589-010-9356-0
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Cites Work
- Smoothing functions and smoothing Newton method for complementarity and variational inequality problems
- A smoothing projected Newton-type algorithm for semi-infinite programming
- Partially finite convex programming. I: Quasi relative interiors and duality theory
- Positive definite functions and generalizations, an historical survey
- A smoothing method for mathematical programs with equilibrium constraints
- \(L_ p\)-spectral estimation with an \(L_ \infty\)-upper bound
- Differentiability and semismoothness properties of integral functions and their applications
- A smoothing Newton method for general nonlinear complementarity problems
- Quadratic convergence of Newton's method for convex interpolation and smoothing
- A new look at smoothing Newton methods for nonlinear complementarity problems and box constrained variational inequalities
- A nonsmooth version of Newton's method
- Convergence rate of Newton's method for \(L_2\) spectral estimation
- Nonsmooth Equations: Motivation and Algorithms
- Spectral estimation for sensor arrays
- Optimization and nonsmooth analysis
- A simple constraint qualification in infinite dimensional programming
- $L_2 $ Spectral Estimation
- A Dual Approach to Multidimensional $L_p$ Spectral Estimation Problems
- Duality Relationships for Entropy-Like Minimization Problems
- Semismooth and Semiconvex Functions in Constrained Optimization
- Some examples of cycling in variable metric methods for constrained minimization
- Semismooth Karush-Kuhn-Tucker Equations and Convergence Analysis of Newton and Quasi-Newton Methods for Solving these Equations
- Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities
- Maximum entropy and maximum likelihood in spectral estimation
- Smoothing Methods and Semismooth Methods for Nondifferentiable Operator Equations
- Convergence Analysis of Some Algorithms for Solving Nonsmooth Equations
- A Newton Method for Shape-Preserving Spline Interpolation
- Convergence of Newton's method for convex best interpolation
- A further result on an implicit function theorem for locally Lipschitz functions
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