Least squares parameter estimation algorithms for non-linear systems

DOI10.1080/00207728408547198zbMath0567.93062OpenAlexW2074667289MaRDI QIDQ3684009

W. S. F. Voon, Stephen A. Billings

Publication date: 1984

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: http://eprints.whiterose.ac.uk/76436/1/report%20225%20%281%29.pdf

zbMATH Keywords

model validationstructure detectionnon-linear systemsinput sensitivityinput signal selectionLeast squares parameter estimation algorithms

Mathematics Subject Classification ID

Related Items (10)

Identification of models for chaotic systems from noisy data: implications for performance and nonlinear filtering ⋮ Non‐linear adaptive control via laguerre expansion of volterra kernels ⋮ Identification of continuous time nonlinear systems using delayed state variable filters ⋮ Adaptive control of nonlinear dynamic systems using \(\theta\)-adaptive neural networks ⋮ Strong consistency and convergence rate of parameter identification for bilinear systems ⋮ Smoothing data with local instabilities for the identification of chaotic systems ⋮ Nonlinearity tests for bilinear systems ⋮ Representations of non-linear systems: the NARMAX model ⋮ Improved parameter estimates for non-linear dynamical models using a bootstrap method ⋮ A bootstrap method for structure detection of NARMAX models

Cites Work

• Polynomial response maps
• Dynamic system identification. Experiment design and data analysis
• Global convergence of output error recursions in colored noise

This page was built for publication: Least squares parameter estimation algorithms for non-linear systems