Minimal condition number for positive definite Hankel matrices using semidefinite programming

DOI10.1016/j.laa.2010.04.052zbMath1209.65050OpenAlexW2038696008WikidataQ114851463 ScholiaQ114851463MaRDI QIDQ989049

Suliman Al-Homidan, Florian A. Potra, Mohammad M. Alshahrani, Cosmin G. Petra

Publication date: 27 August 2010

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2010.04.052

zbMATH Keywords

semi-definite programmingminimum condition numberpositive definite real Hankel matrix

Mathematics Subject Classification ID

Semidefinite programming (90C22) Numerical computation of matrix norms, conditioning, scaling (65F35) Conditioning of matrices (15A12) Toeplitz, Cauchy, and related matrices (15B05)

Related Items (1)

A class of weighted low rank approximation of the positive semidefinite Hankel matrix

Uses Software

• Mathematica
• SDPHA
• SDPA
• SeDuMi
• SDPT3

Cites Work

• Solving Hankel matrix approximation problem using semidefinite programming
• How bad are Hankel matrices?
• Positive definite Hankel matrices of minimal condition
• The condition number of real Vandermonde, Krylov and positive definite Hankel matrices
• Hybrid methods for approximating Hankel matrix
• On homogeneous interrior-point algorithms for semidefinite programming
• SDPT3 — A Matlab software package for semidefinite programming, Version 1.3
• Sdpha: a Matlab implementation of homogeneous interior-point algorithms for semidefinite programming
• Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
• Stable factorization for Hankel and Hankel‐like matrices
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Minimal condition number for positive definite Hankel matrices using semidefinite programming