The normalized least-squares order-recursive lattice smoother

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 t...

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Vydané v:Signal processing Ročník 82; číslo 6; s. 895 - 905
Hlavní autori: Kim, Dong Kyoo, Park, PooGyeon
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 01.06.2002
Elsevier Science
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ISSN:0165-1684, 1872-7557
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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.
AbstractList 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.
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. copyright 2002 Elsevier Science B.V. All rights reserved.
Author Park, PooGyeon
Kim, Dong Kyoo
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10.1109/78.757234
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10.1109/TCS.1981.1085020
10.1109/PROC.1982.12407
10.1145/1478786.1478840
10.1109/TCOM.1981.1094968
10.1109/ICASSP.1981.1171234
10.1109/78.382393
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Issue 6
Keywords Least-squares lattice algorithms
Smoothing algorithms
Order-recursive structures
Adaptive filters
Geometric interpretation
Normalized LSORL smoothers
Finite precision arithmetic
Simulation
Least squares method
Adaptive filtering
Recursive method
Signal processing
Geometrical method
Algorithm
Lattice structure
Language English
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Snippet This paper introduces a variance- and angle-normalized version of the least-squares order-recursive lattice (LSORL) smoother, say the normalized LSORL...
This paper introduces a variance- and angle-normalized version of the least-squares order-recursive lattice (LSORL) smoother, say the normalized LSORL...
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SubjectTerms Adaptive filters
Applied sciences
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Finite precision arithmetic
Geometric interpretation
Information, signal and communications theory
Least-squares lattice algorithms
Normalized LSORL smoothers
Order-recursive structures
Signal and communications theory
Signal, noise
Smoothing algorithms
Telecommunications and information theory
Title The normalized least-squares order-recursive lattice smoother
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