Recursive least-squares and accelerated convergence in stochastic approximation schemes

DOI10.1002/acs.649zbMath1153.93536OpenAlexW2156620561WikidataQ59591979 ScholiaQ59591979MaRDI QIDQ2722623

Lennart Ljung

Publication date: 2 July 2001

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-55752

zbMATH Keywords

stochastic approximationtime-varying parametersrecursive least squareslinear regression model

Mathematics Subject Classification ID

Least squares and related methods for stochastic control systems (93E24) Stochastic approximation (62L20)

Related Items (3)

Asymptotically optimal smoothing of averaged LMS estimates for regression parameter tracking ⋮ Recursive identification of time-varying systems: self-tuning and matrix RLS algorithms ⋮ Semimartingale stochastic approximation procedure and recursive estimation

Cites Work

• Unnamed Item
• Unnamed Item
• Adaptation and tracking in system identification - a survey
• Stochastic Approximation with Averaging of the Iterates: Optimal Asymptotic Rate of Convergence for General Processes
• A result on the mean square error obtained using general tracking algorithms
• Acceleration of Stochastic Approximation by Averaging
• Performance analysis of general tracking algorithms

This page was built for publication: Recursive least-squares and accelerated convergence in stochastic approximation schemes