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

DOI10.1155/2015/937573zbMath1347.65105OpenAlexW2092674423WikidataQ59112072 ScholiaQ59112072MaRDI QIDQ305468

Xuewei Zhang, Kexin Cheng, Jianchao Bai, Xue-Feng Duan

Publication date: 30 August 2016

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/937573

zbMATH Keywords

unconstrained optimizationnumerical examplessignal processingArmijo line searchnonlinear conjugate gradient algorithmsemidefinite Hankel matrix

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (1)

A novel method for a class of structured low-rank minimizations with equality constraint

Cites Work

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• Minimal condition number for positive definite Hankel matrices using semidefinite programming
• Factorization of finite rank Hankel and Toeplitz matrices
• Positive definite Hankel matrices of minimal condition
• Hybrid methods for approximating Hankel matrix
• Low rank approximation of a Hankel matrix by structured total least norm
• Hankel matrices for system identification
• The Solution to a Structured Matrix Approximation Problem Using GrassmanCoordinates
• Approximation of Large-Scale Dynamical Systems

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