Normalized lattice algorithms for least-squares FIR system identification
Copyright policy )Normalized lattice algorithms for least-squares FIR system identification
Recently developed algorithms [see \textit{M. Morf}, \textit{B. Dickinson}, \textit{A. Vieira} and the second author, ibid. 25, 429-433 (1977; Zbl 0373.93043)] 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.
- Stanford University United States
- Information Systems Laboratories (United States) United States
- Rafael Advanced Defense Systems (Israel) Israel
Discrete-time control/observation systems, Computational methods in stochastic control, Identification in stochastic control theory, Analysis of algorithms and problem complexity, square-root normalized lattice algorithms, finite impulse-response models, Model systems in control theory, Inference from stochastic processes and prediction, least-squares identification
Discrete-time control/observation systems, Computational methods in stochastic control, Identification in stochastic control theory, Analysis of algorithms and problem complexity, square-root normalized lattice algorithms, finite impulse-response models, Model systems in control theory, Inference from stochastic processes and prediction, least-squares identification
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