Weight of Pole in Autoregressive Type Model

Kuniharu KISHIDA; Sumasu YAMADA; Nobuo SUGIBAYASHI

Weight of Pole in Autoregressive Type Model

Kuniharu KISHIDA, Sumasu YAMADA, Nobuo SUGIBAYASHI

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An AR model is one of linear stochastic equations, which is characterized by the eigenvalues and eigenvectors. Since the poles in the AR model correspond to the eigenvalues in linear equations, the weights of poles in the AR model correspond to the eigenvectors in linear equations. The AR type model has essentially two types poles; system poles and virtual poles corresponding to system zeros. These poles can be distinguished by observing the weight of each pole in the partial fraction expansion of the AR model transfer function. The rules for separation of AR poles are: (a) If the weight of an AR pole is constant for AR model order change, the AR pole is a system pole. (b) If the weight of that is inversely proportional to the AR model order, the AR pole is one of virtual poles.

Publication: IEICE TRANSACTIONS on transactions Vol.E72-E No.5 pp.514-520

Publication Date: 1989/05/25

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Type of Manuscript: Special Section PAPER (Special Issue on Information Theory and Its Applications)

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Kuniharu KISHIDA
Sumasu YAMADA
Nobuo SUGIBAYASHI

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Kuniharu KISHIDA, Sumasu YAMADA, Nobuo SUGIBAYASHI, "Weight of Pole in Autoregressive Type Model" in IEICE TRANSACTIONS on transactions, vol. E72-E, no. 5, pp. 514-520, May 1989, doi: .
Abstract: An AR model is one of linear stochastic equations, which is characterized by the eigenvalues and eigenvectors. Since the poles in the AR model correspond to the eigenvalues in linear equations, the weights of poles in the AR model correspond to the eigenvectors in linear equations. The AR type model has essentially two types poles; system poles and virtual poles corresponding to system zeros. These poles can be distinguished by observing the weight of each pole in the partial fraction expansion of the AR model transfer function. The rules for separation of AR poles are: (a) If the weight of an AR pole is constant for AR model order change, the AR pole is a system pole. (b) If the weight of that is inversely proportional to the AR model order, the AR pole is one of virtual poles.
URL: https://global.ieice.org/en_transactions/transactions/10.1587/e72-e_5_514/_p

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@ARTICLE{e72-e_5_514,
author={Kuniharu KISHIDA, Sumasu YAMADA, Nobuo SUGIBAYASHI, },
journal={IEICE TRANSACTIONS on transactions},
title={Weight of Pole in Autoregressive Type Model},
year={1989},
volume={E72-E},
number={5},
pages={514-520},
abstract={An AR model is one of linear stochastic equations, which is characterized by the eigenvalues and eigenvectors. Since the poles in the AR model correspond to the eigenvalues in linear equations, the weights of poles in the AR model correspond to the eigenvectors in linear equations. The AR type model has essentially two types poles; system poles and virtual poles corresponding to system zeros. These poles can be distinguished by observing the weight of each pole in the partial fraction expansion of the AR model transfer function. The rules for separation of AR poles are: (a) If the weight of an AR pole is constant for AR model order change, the AR pole is a system pole. (b) If the weight of that is inversely proportional to the AR model order, the AR pole is one of virtual poles.},
keywords={},
doi={},
ISSN={},
month={May},}

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TY - JOUR
TI - Weight of Pole in Autoregressive Type Model
T2 - IEICE TRANSACTIONS on transactions
SP - 514
EP - 520
AU - Kuniharu KISHIDA
AU - Sumasu YAMADA
AU - Nobuo SUGIBAYASHI
PY - 1989
DO -
JO - IEICE TRANSACTIONS on transactions
SN -
VL - E72-E
IS - 5
JA - IEICE TRANSACTIONS on transactions
Y1 - May 1989
AB - An AR model is one of linear stochastic equations, which is characterized by the eigenvalues and eigenvectors. Since the poles in the AR model correspond to the eigenvalues in linear equations, the weights of poles in the AR model correspond to the eigenvectors in linear equations. The AR type model has essentially two types poles; system poles and virtual poles corresponding to system zeros. These poles can be distinguished by observing the weight of each pole in the partial fraction expansion of the AR model transfer function. The rules for separation of AR poles are: (a) If the weight of an AR pole is constant for AR model order change, the AR pole is a system pole. (b) If the weight of that is inversely proportional to the AR model order, the AR pole is one of virtual poles.
ER -