On the convergence of pseudo-linear regression algorithms

DOI10.1080/0020718508961207zbMath0581.93057OpenAlexW1985332501MaRDI QIDQ3705323

Göte Solbrand, Petre Stoica, Anders Ahlén, Torsten Söderström

Publication date: 1985

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/0020718508961207

zbMATH Keywords

stabilityconvergence propertiespseudo-linear regression algorithm

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Estimation and detection in stochastic control theory (93E10)

Related Items (4)

Direct and indirect least squares methods in continuous-time parameter estimation ⋮ ITERATIVE AND RECURSIVE ESTIMATION OF TRANSFER FUNCTIONS ⋮ A covariance matching approach for identifying errors-in-variables systems ⋮ Convergence analysis of an adaptive pseudolinear-regression notch filtering algorithm

Cites Work

• A theoretical analysis of recursive identification methods
• Eigenvalue location of certain matrices arising in convergence analysis problems
• Rapid parameter estimation algorithms using the ELS principle
• The structure of simultaneous equations estimators
• On the asymptotic accuracy of pseudo-linear regression algorithms
• The convergence of AML
• Counterexamples to general convergence of a commonly used recursive identification method
• On least squares algorithms for system parameter identification
• On positive real transfer functions and the convergence of some recursive schemes
• Least Squares Variant of the Dhrymes Two-Step Estimation Procedure of the Distributed Lag Model

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