The Asymptotic Local Approach to Change Detection and Model Validation

Albert Benveniste; Michele Basseville; Georges V. Moustakides

doi:10.1109/TAC.1987.1104683

The Asymptotic Local Approach to Change Detection and Model Validation

Albert Benveniste, Michele Basseville, Georges V. Moustakides

Research output: Contribution to journal › Article › peer-review

153 Scopus citations

Abstract

We present a systematic approach for the design of change detection and model validation algorithms for dynamical systems. We show how to associate to any identification algorithm a change detection and a model validation procedure, which are optimal in some asymptotic sense. The foundations of our method go back to the asymptotic local approach in statistics, and our method generalizes this approach.

Original language	English (US)
Pages (from-to)	583-592
Number of pages	10
Journal	IEEE Transactions on Automatic Control
Volume	32
Issue number	7
DOIs	https://doi.org/10.1109/TAC.1987.1104683
State	Published - Jul 1987
Externally published	Yes

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TAC.1987.1104683

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title = "The Asymptotic Local Approach to Change Detection and Model Validation",

abstract = "We present a systematic approach for the design of change detection and model validation algorithms for dynamical systems. We show how to associate to any identification algorithm a change detection and a model validation procedure, which are optimal in some asymptotic sense. The foundations of our method go back to the asymptotic local approach in statistics, and our method generalizes this approach.",

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AU - Basseville, Michele

AU - Moustakides, Georges V.

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N2 - We present a systematic approach for the design of change detection and model validation algorithms for dynamical systems. We show how to associate to any identification algorithm a change detection and a model validation procedure, which are optimal in some asymptotic sense. The foundations of our method go back to the asymptotic local approach in statistics, and our method generalizes this approach.

AB - We present a systematic approach for the design of change detection and model validation algorithms for dynamical systems. We show how to associate to any identification algorithm a change detection and a model validation procedure, which are optimal in some asymptotic sense. The foundations of our method go back to the asymptotic local approach in statistics, and our method generalizes this approach.

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EP - 592

JO - IEEE Transactions on Automatic Control

JF - IEEE Transactions on Automatic Control

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The Asymptotic Local Approach to Change Detection and Model Validation

Abstract

All Science Journal Classification (ASJC) codes

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