Title :
Unified derivation and initial convergence of three prewindowed fast transversal recursive least squares algorithms
Author_Institution :
AT&T Data Commun., Middletown, NJ, USA
fDate :
7/1/1988 12:00:00 AM
Abstract :
Three prewindowed transversal fast RLS (recursive least-squares) algorithms, the FK (fast Kalman), FAEST (fast a posteriori estimation sequential technique), and FTF (fast transversal filter) algorithms, are derived in a unified approach. It is shown 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
Keywords :
convergence; digital simulation; estimation theory; filtering and prediction theory; least squares approximations; FAEST; FK; FTF; RLS; algorithmic forgetting factor; computer simulations; fast Kalman; fast a posteriori estimation sequential technique; fast transversal filter; initial convergence; prewindowed fast transversal recursive least squares algorithms; unified derivation; Circuits; Computer simulation; Conformal mapping; Controllability; Convergence; Filters; Image processing; Kalman filters; MIMO; Observability; Recursive estimation; Resonance light scattering; State-space methods; Testing; Transversal filters;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on