Performance Enhancement of the Recursive Least Squares Algorithms with Rank Two Updates
Optimization and Control
2025-07-16 v1 Information Theory
Numerical Analysis
Dynamical Systems
History and Overview
math.IT
Numerical Analysis
Abstract
New recursive least squares algorithms with rank two updates (RLSR2) that include both exponential and instantaneous forgetting (implemented via a proper choice of the forgetting factor and the window size) are introduced and systematically associated in this report with well-known RLS algorithms with rank one updates. Moreover, new properties (which can be used for further performance improvement) of the recursive algorithms associated with the convergence of the inverse of information matrix and parameter vector are established in this report. The performance of new algorithms is examined in the problem of estimation of the grid events in the presence of significant harmonic emissions.
Keywords
Cite
@article{arxiv.2507.11095,
title = {Performance Enhancement of the Recursive Least Squares Algorithms with Rank Two Updates},
author = {Alexander Stotsky},
journal= {arXiv preprint arXiv:2507.11095},
year = {2025}
}
Comments
7pages, 2 figures