Unified derivation and initial convergence of three prewindowed fast transversal recursive least squares algorithms
Copyright policy )Unified derivation and initial convergence of three prewindowed fast transversal recursive least squares algorithms
The three prewindowed transversal fast RLS algorithms, the FK (fast Kalman), FAEST (fast a posteriori estimation sequential technique), and FTF (fast transversal filter) algorithms are derived in a unified approach. We show that their mathematical equivalence can be established only by properly choosing their initial conditions. It is confirmed by computer simulations that the choice of initial conditions and the algorithmic forgetting factor could strongly affect the speed of the initial convergence.
- AT&T United States
Finite difference methods for boundary value problems involving PDEs, Estimation and detection in stochastic control theory, convergence, Computational methods in stochastic control, Filtering in stochastic control theory, unified approach, forgetting factor, Sequential estimation, prewindowed transversal fast RLS algorithms, computer simulations
Finite difference methods for boundary value problems involving PDEs, Estimation and detection in stochastic control theory, convergence, Computational methods in stochastic control, Filtering in stochastic control theory, unified approach, forgetting factor, Sequential estimation, prewindowed transversal fast RLS algorithms, computer simulations
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