A least squares approach to reduce stable discrete linear systems preserving their stability.

DOI10.1016/j.laa.2003.11.010zbMath1135.93019OpenAlexW2040244327MaRDI QIDQ1430377

Sven Feldmann, Patrick M. Lang

Publication date: 27 May 2004

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

Full work available at URL: https://doi.org/10.1016/j.laa.2003.11.010

zbMATH Keywords

StabilityStein equationmatrixHankelModel reductionDiscrete linear systems

Mathematics Subject Classification ID

Discrete-time control/observation systems (93C55) Lyapunov and other classical stabilities (Lagrange, Poisson, (L^p, l^p), etc.) in control theory (93D05) Linear systems in control theory (93C05)

Related Items (1)

A unified least squares approach to identify and to reduce continuous asymptotically stable systems

Cites Work

• Unnamed Item
• Unnamed Item
• On minimality in the partial realization problem
• On parametrizations for the minimal partial realization problem
• A generalized minimal partial realization problem
• On minimal realizations: A polynomial approach
• On the partial realization problem
• QR factorization of Toeplitz matrices
• Padé techniques for model reduction in linear system theory: a survey
• An algebraic approach to the partial realization problem
• Downdating of Szegö polynomials and data-fitting applications
• Kernel structure of block Hankel and Toeplitz matrices and partial realization
• Parametrization of minimal rank block Hankel matrix extensions and minimal partial realizations
• Inversion of a generalized block Loewner matrix, the minimal partial realization, and matrix rational interpolation problem
• Uniqueness properties of minimal partial realizations
• Krylov-subspace methods for reduced-order modeling in circuit simulation
• Recursive partial realization from the combined sequence of Markov parameters and moments
• A canonical matrix continued fraction solution of the minimal (partial) realization problem
• A superfast method for solving Toeplitz linear least squares problems.
• High performance algorithms for Toeplitz and block Toeplitz matrices
• A Stabilized Superfast Solver for Nonsymmetric Toeplitz Systems
• The Sequential Construction of Minimal Partial Realizations from Finite Input–Output Data
• Stable partial Padé approximations for reduced-order trnsfer functions
• An improved error estimate for reduced-order models of discrete-time systems
• Balanced realizations: canonical form, parametrization, model reduction
• Superfast Solution of Real Positive Definite Toeplitz Systems
• New Fast Algorithms for Structured Linear Least Squares Problems
• Small-signal circuit analysis and sensitivity computations with the PVL algorithm
• Stable and Efficient Algorithms for Structured Systems of Linear Equations
• Fast Gaussian Elimination with Partial Pivoting for Matrices with Displacement Structure
• A partial Padé-via-Lanczos method for reduced-order modeling

This page was built for publication: A least squares approach to reduce stable discrete linear systems preserving their stability.