The normalized least-squares order-recursive lattice smoother

Authors:
Dong Kyoo Kim;PooGyeon Park
Affiliations:
Division of Electrical and Computer Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, Kyung-buk, 790-784 Pohang, South Korea;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, Kyung-buk, 790-784 Pohang, South Korea
Venue:
Signal Processing
Year:
2002

Citing 4
Cited 1

A unifed view of parametric processing algorithms for prewindowed signals

Signal Processing
Adaptive filter theory (3rd ed.)

Adaptive filter theory (3rd ed.)
Least squares order-recursive lattice smoothers

IEEE Transactions on Signal Processing
A modified QRD for smoothing and a QRD-LSL smoothing algorithm

IEEE Transactions on Signal Processing

Network numerical analysis for the smoother and the lagged joint-process estimator

The Journal of Supercomputing

Quantified Score

Hi-index	0.08

Visualization

Abstract

This paper introduces a variance- and angle-normalized version of the least-squares order-recursive lattice (LSORL) smoother, say the normalized LSORL smoother, via a geometric approach. The normalized LSORL smoother has excellent round-off noise properties and inherits all the other advantages of the normalized LSORL as well. Simulation results show that the normalized LSORL smoother outperforms the existing LSORL and QRD-based least-squares lattice smoother algorithms when finite-precision arithmetic is used.