Title :
Tracking improvements in fast RLS algorithms using a variable forgetting factor
Author :
Toplis, Blake ; Pasupathy, Subbarayan
Author_Institution :
Bell-Northern Res., Montreal, Que., Canada
fDate :
2/1/1988 12:00:00 AM
Abstract :
The concept of a variable forgetting factor (VFF) is incorporated into fast recursive least-squares (FRLS) algorithms. Compromises in the data matrix that are needed to do this are examined. Both prewindowed and growing memory covariance algorithms are presented in transversal and lattice structures. Forgetting-factor adaptation schemes, which improve tracking performance over conventional FRLS algorithms, are suggested. Finally, the bias introduced by the use of the VFF is analyzed
Keywords :
filtering and prediction theory; least squares approximations; adaptive filtering; covariance algorithms; data matrix; fast RLS algorithms; fast recursive least-squares; lattice structures; tracking performance; transversal structure; variable forgetting factor; Adaptive filters; Arithmetic; Cost function; Covariance matrix; Lattices; Least squares methods; Matched filters; Resonance light scattering; Statistics; Working environment noise;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
