Asymptotic Uncertainty of Transfer Function Estimates Using Non-Parametric Noise Models

Rik Pintelon; M. Hong

Asymptotic Uncertainty of Transfer Function Estimates Using Non-Parametric Noise Models

Rik Pintelon, M. Hong

Electricity

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

1 Citation (Scopus)

Abstract

Identification of parametric transfer function models from noisy input/output observations is an important task in many engineering applications. Besides the parametric model, the estimation algorithm used should also provide accurate confidence bounds. In addition it is important to know whether the proposed estimation algorithm has the lowest possible uncertainty within the class of consistent estimators. This paper handles these issues for the frequency domain Gaussian maximum likelihood estimator of rational transfer function models.

Original language	English
Title of host publication	IMTC/2007, Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Warsaw, Poland, May 1-3, 2007
Publication status	Published - 1 May 2007
Event	Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet - Stockholm, Sweden Duration: 21 Sept 2009 → 25 Sept 2009

Conference

Conference	Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet
Country/Territory	Sweden
City	Stockholm
Period	21/09/09 → 25/09/09

Keywords

non-parametric noise modelling

IEEE/IMTC 2007, the IEEE Instrumentation and Measurement Technology Conference
Laurent Vanbeylen (Speaker)
1 May 2007 → 3 May 2007
Activity: Talk or presentation › Talk or presentation at a conference
IEEE/IMTC 2007, the IEEE Instrumentation and Measurement Technology Conference
Rik Pintelon (Speaker)
1 May 2007 → 3 May 2007
Activity: Talk or presentation › Talk or presentation at a conference
IEEE/IMTC 2007, the IEEE Instrumentation and Measurement Technology Conference
Liesbeth Gomme (Speaker)
1 May 2007 → 3 May 2007
Activity: Talk or presentation › Talk or presentation at a conference

Cite this

@inproceedings{cbce38cc32dc4b0abc8a9ce184b00342,

title = "Asymptotic Uncertainty of Transfer Function Estimates Using Non-Parametric Noise Models",

abstract = "Identification of parametric transfer function models from noisy input/output observations is an important task in many engineering applications. Besides the parametric model, the estimation algorithm used should also provide accurate confidence bounds. In addition it is important to know whether the proposed estimation algorithm has the lowest possible uncertainty within the class of consistent estimators. This paper handles these issues for the frequency domain Gaussian maximum likelihood estimator of rational transfer function models.",

keywords = "non-parametric noise modelling",

author = "Rik Pintelon and M. Hong",

year = "2007",

month = may,

day = "1",

language = "English",

isbn = "1-4244-0589-0",

booktitle = "IMTC/2007, Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Warsaw, Poland, May 1-3, 2007",

note = "Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet ; Conference date: 21-09-2009 Through 25-09-2009",

}

TY - GEN

T1 - Asymptotic Uncertainty of Transfer Function Estimates Using Non-Parametric Noise Models

AU - Pintelon, Rik

AU - Hong, M.

PY - 2007/5/1

Y1 - 2007/5/1

N2 - Identification of parametric transfer function models from noisy input/output observations is an important task in many engineering applications. Besides the parametric model, the estimation algorithm used should also provide accurate confidence bounds. In addition it is important to know whether the proposed estimation algorithm has the lowest possible uncertainty within the class of consistent estimators. This paper handles these issues for the frequency domain Gaussian maximum likelihood estimator of rational transfer function models.

AB - Identification of parametric transfer function models from noisy input/output observations is an important task in many engineering applications. Besides the parametric model, the estimation algorithm used should also provide accurate confidence bounds. In addition it is important to know whether the proposed estimation algorithm has the lowest possible uncertainty within the class of consistent estimators. This paper handles these issues for the frequency domain Gaussian maximum likelihood estimator of rational transfer function models.

KW - non-parametric noise modelling

M3 - Conference paper

SN - 1-4244-0589-0

BT - IMTC/2007, Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Warsaw, Poland, May 1-3, 2007

T2 - Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet

Y2 - 21 September 2009 through 25 September 2009

ER -

Asymptotic Uncertainty of Transfer Function Estimates Using Non-Parametric Noise Models

Abstract

Conference

Keywords

Fingerprint

Activities

IEEE/IMTC 2007, the IEEE Instrumentation and Measurement Technology Conference

IEEE/IMTC 2007, the IEEE Instrumentation and Measurement Technology Conference

IEEE/IMTC 2007, the IEEE Instrumentation and Measurement Technology Conference

Cite this