A Unified Approach to Structured Covariances: Fast Generalized Sliding Window RLS Recursions for Arbitrary Basis

This paper extends the existing fast RLS recursions originally intended to exponentially windowed problems for general models, to a generalized sliding window formulation (GSWRLS). From a matrix algebra perspective, we show explicitly how the displacement rank of the underlying inverse covariance ma...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 61; H. 23; S. 6060 - 6075
1. Verfasser:	Merched, Ricardo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.12.2013 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Applied sciences Covariance matrices Data structures Detection, estimation, filtering, equalization, prediction Exact sciences and technology Information, signal and communications theory lattice Matrix decomposition orthonormal model Polynomials regularized least-squares Signal and communications theory Signal processing Signal processing algorithms Signal, noise Sliding window RLS algorithm Telecommunications and information theory Breakpoint Recurrence orthonormal model Matrix algebra Generating function Equalizer Covariance matrix Recursive algorithm Kernel method Covariance Inverse matrix Least squares method First order lattice regularized least-squares Signal processing Sliding window RLS algorithm Data structure
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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