Robustness of autoregressive systems

M. S. Ravi; Joachim Rosenthal; Xiaochang Wang

Robustness of autoregressive systems

M. S. Ravi, Joachim Rosenthal, Xiaochang Wang

Mathematics and Statistics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this short note we intend to give a quantitative basis for the intuitive principle that 'small perturbations' in the parameters of a system do not affect its stability. We also indicate a method of defining a metric on the space of all autoregressive systems of McMillan degree at most n.

Original language	English
Title of host publication	Proceedings of the IEEE Conference on Decision and Control
Editors	Anon
Publisher	Publ by IEEE
Pages	2878-2879
Number of pages	2
ISBN (Print)	0780312988
State	Published - 1993
Event	Proceedings of the 32nd IEEE Conference on Decision and Control. Part 3 (of 4) - San Antonio, TX, USA Duration: Dec 15 1993 → Dec 17 1993

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	3
ISSN (Print)	0191-2216

Conference

Conference	Proceedings of the 32nd IEEE Conference on Decision and Control. Part 3 (of 4)
City	San Antonio, TX, USA
Period	12/15/93 → 12/17/93

Cite this

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title = "Robustness of autoregressive systems",

abstract = "In this short note we intend to give a quantitative basis for the intuitive principle that 'small perturbations' in the parameters of a system do not affect its stability. We also indicate a method of defining a metric on the space of all autoregressive systems of McMillan degree at most n.",

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note = "Proceedings of the 32nd IEEE Conference on Decision and Control. Part 3 (of 4) ; Conference date: 15-12-1993 Through 17-12-1993",

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AU - Ravi, M. S.

AU - Rosenthal, Joachim

AU - Wang, Xiaochang

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N2 - In this short note we intend to give a quantitative basis for the intuitive principle that 'small perturbations' in the parameters of a system do not affect its stability. We also indicate a method of defining a metric on the space of all autoregressive systems of McMillan degree at most n.

AB - In this short note we intend to give a quantitative basis for the intuitive principle that 'small perturbations' in the parameters of a system do not affect its stability. We also indicate a method of defining a metric on the space of all autoregressive systems of McMillan degree at most n.

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M3 - Conference contribution

AN - SCOPUS:0027748428

SN - 0780312988

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 2878

EP - 2879

BT - Proceedings of the IEEE Conference on Decision and Control

A2 - Anon, null

PB - Publ by IEEE

T2 - Proceedings of the 32nd IEEE Conference on Decision and Control. Part 3 (of 4)

Y2 - 15 December 1993 through 17 December 1993

ER -

Robustness of autoregressive systems

Abstract

Publication series

Conference

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