Normalized lattice algorithms for least-squares FIR system identification

Recently developed algorithms for least-squares identification of autoregressive models are extended in this paper so as to facilitate least-squares identification of finite impulse-response models. The algorithms belong to the class of square-root normalized lattice algorithms, hence they share the...

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Vydáno v:IEEE transactions on acoustics, speech, and signal processing Ročník 31; číslo 1; s. 122 - 128
Hlavní autoři: Porat, B., Kailath, T.
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.01.1983
Témata:
Computational efficiency
Contracts
Equations
Finite impulse response filter
Information systems
Laboratories
Lattices
Prediction algorithms
Smoothing methods
System identification
ISSN:0096-3518
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Shrnutí:Recently developed algorithms for least-squares identification of autoregressive models are extended in this paper so as to facilitate least-squares identification of finite impulse-response models. The algorithms belong to the class of square-root normalized lattice algorithms, hence they share the computational efficiency and good numerical behavior of the latter. Two versions are presented-one for identifying time-invariant models and the other for tracking time-varying parameters. New lattice-form realizations of the identified FIR models are given. The general framework is then specialized to the important cases of prediction and smoothing.
ISSN:0096-3518
DOI:10.1109/TASSP.1983.1164012