A two-dimensional fast lattice recursive least squares algorithm

This paper is mainly devoted to the derivation of a new two-dimensional fast lattice recursive least squares (2D FLRLS) algorithm. This algorithm updates the filter coefficients in growing-order form with linear computational complexity. After appropriately defining the "order" of 2D data...

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Veröffentlicht in:IEEE transactions on signal processing Jg. 44; H. 10; S. 2557 - 2567
Hauptverfasser: Xiang Liu, Najim, M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.10.1996
Institute of Electrical and Electronics Engineers
Schlagworte:
Applied sciences
Computational complexity
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Information, signal and communications theory
Lattices
Least squares methods
Nonlinear filters
Reflection
Resonance light scattering
Signal and communications theory
Signal processing algorithms
Signal, noise
System identification
Telecommunications and information theory
Transversal filters
Two dimensional displays
Recursive method
Signal processing
Fast algorithm
Least squares method
Signal estimation
Prediction
ISSN:1053-587X
Online-Zugang:Volltext
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Zusammenfassung:This paper is mainly devoted to the derivation of a new two-dimensional fast lattice recursive least squares (2D FLRLS) algorithm. This algorithm updates the filter coefficients in growing-order form with linear computational complexity. After appropriately defining the "order" of 2D data and exploiting the relation with 1D multichannel, "order" recursion relations and shift invariance property are derived. The geometrical approaches of the vector space and the orthogonal projection then can be used for solving this 2D prediction problem. We examine the performances of this new algorithm in comparison with other fast algorithms.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:1053-587X
DOI:10.1109/78.539039