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Autoregressive models of singular spectral matrices

Authors: Anderson, Brian; Deistler, Manfred; Chen, Weitian; Filler, Alexander;

Autoregressive models of singular spectral matrices

Abstract

This paper deals with autoregressive (AR) models of singular spectra, whose corresponding transfer function matrices can be expressed in a stable AR matrix fraction description [Formula: see text] with [Formula: see text] a tall constant matrix of full column rank and with the determinantal zeros of [Formula: see text] all stable, i.e. in [Formula: see text]. To obtain a parsimonious AR model, a canonical form is derived and a number of advantageous properties are demonstrated. First, the maximum lag of the canonical AR model is shown to be minimal in the equivalence class of AR models of the same transfer function matrix. Second, the canonical form model is shown to display a nesting property under natural conditions. Finally, an upper bound is provided for the total number of real parameters in the obtained canonical AR model, which demonstrates that the total number of real parameters grows linearly with the number of rows in [Formula: see text].

Countries
Austria, Australia
Keywords

Keywords: AR models, Canonical structure, Brief Paper, Equivalence classes, Ar-matrix, Matrix algebra, Upper Bound, canonical form, Spectral matrices, 539, Natural conditions, Stochastic systems in control theory (general), Electrical and Electronic Engineering, Computer simulatio Autoregressive (AR) model, Eigenvalue problems, Auto regressive models, Canonical form, Autoregressive (AR) model, Transfer function matrix, Constant matrix, autoregressive (AR) model, Matrix fraction description, Control and Systems Engineering, matrix fraction description, Column ranks

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Average
Green
hybrid