Journal ArticleDOI
Error Propagation Properties of Recursive Least Squares Adaptation Algorithms
Stefan Ljung,Lennart Ljung +1 more
TLDR
The fast least squares al gorithm, sometimes known as the “fast Kalman algorithm” is however shown to be un stabl e with res pect to such errors, i.e. the effect of the error decays exponentially.About:
This article is published in IFAC Proceedings Volumes.The article was published on 1984-07-01. It has received 9 citations till now. The article focuses on the topics: Recursive least squares filter.read more
Citations
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Proceedings ArticleDOI
Reconciling fast RLS lattice and QR algorithms
TL;DR: It is shown that the FQR algorithms and the FLA algorithms are essentially the same group of algorithms and that it is basically only the way in which these algorithms are derived that makes them appear to be different.
Journal ArticleDOI
Numerical stability improvements of state-value function approximations based on RLS learning for online HDP-DLQR control system design
TL;DR: The developed learning strategy is designed to provide computational performance improvements, which aim at making possible the real time implementations of optimal control design methodology based upon actor-critic reinforcement learning paradigms.
Proceedings ArticleDOI
Numerical stability issues of the conventional recursive least squares algorithm
A.P. Liavas,Phillip A. Regalia +1 more
TL;DR: Borders for the relative precision of the computations and the accumulated round-off error are derived, which guarantee the numerical stability of the finite-precision implementation of the conventional RLS algorithm.
Journal ArticleDOI
On the Dynamics of Recursive Least-Squares and Lattices
TL;DR: In this paper, the dynamics of recursive least squares and least-squares lattice parameter estimation algorithms are analyzed. And the authors show that the rate of convergence is exponential and decreases with increasing system order.
Proceedings ArticleDOI
Subspace method optimized for tracking real-valued sinusoids in noise
S. Slavnicu,S. Ciochina +1 more
TL;DR: A novel combination of strong adaptive covariance matrix update and optimized block processing for frequency values retrieval is proposed, which brings a significant reduction in arithmetical complexity at the same level of accuracy.
References
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Journal ArticleDOI
Recursive least squares ladder estimation algorithms
TL;DR: A Hilbert space approach to the derivations of magnitude normalized signal and gain recursions is presented and normalized forms are expected to have even better numerical properties than the unnormalized versions.
Journal ArticleDOI
Fast calculation of gain matrices for recursive estimation schemes
TL;DR: In this paper, the authors presented a method of calculating these vectors with proportional-to-Np operations and memory locations, in contrast to the conventional way which requires proportional-top-N 2 operations and Np memory locations.
Journal ArticleDOI
Exponential convergence of adaptive identification and control algorithms
TL;DR: Output and equation error adaptive identification algorithms and an adaptive control algorithm are shown to be exponentially convergent under a deterministic or stochastic persistently exciting condition on the reference trajectory together with some standard conditions.
Proceedings ArticleDOI
A continuously-adaptive filter implemented as a lattice structure
TL;DR: It is suggested that the successive orthogonalization offered by the lattice may provide convergence advantages not obtainable with tapped-delay-line methods.
Fast Algorithms for Integral Equations and Least Squares Identification Problems
TL;DR: This work is concerned with fast algorithms for integral equations and least squares identification problems and a fast algorithm for solvency identification problems is presented.
Related Papers (5)
Paper: Error propagation properties of recursive least-squares adaptation algorithms
Stefan Ljung,Lennart Ljung +1 more