Greedy Search Method for Separable Nonlinear Models Using Stage Aitken Gradient Descent and Least Squares Algorithms

DOI10.1109/TAC.2022.3214474OpenAlexW4312280089MaRDI QIDQ6093236

Author name not available (Why is that?)

Publication date: 6 October 2023

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tac.2022.3214474

zbMATH Keywords

parameter estimationconvergence ratehierarchical identification algorithmAitken acceleration techniqueseparable nonlinear model

Mathematics Subject Classification ID

Systems theory; control (93-XX)

Related Items (1)

Variable projection algorithms with sparse constraint for separable nonlinear models

Recommendations

• Title not available (Why is that?) 👍 👎
• Title not available (Why is that?) 👍 👎
• A non-linear nested partial least-squares algorithm 👍 👎
• Sieve least squares estimation for partially nonlinear models 👍 👎
• An efficient line search for nonlinear least squares 👍 👎
• An efficient algorithm for the separable nonlinear least squares problem 👍 👎
• A hybrid global optimization algorithm for nonlinear least squares regression 👍 👎
• Efficient parameters estimation method for the separable nonlinear least squares problem 👍 👎
• Matricial gradient for the least-squares residual and its application to optimal model fitting 👍 👎

This page was built for publication: Greedy Search Method for Separable Nonlinear Models Using Stage Aitken Gradient Descent and Least Squares Algorithms

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6093236)