Stochastic unobserved component models for adaptive signal extraction and forecasting

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Published

Standard

Stochastic unobserved component models for adaptive signal extraction and forecasting. / Young, Peter C.; Tych, Wlodek; Pedregal, Diego J.
1998. 234-243 Paper presented at Proceedings of the 1998 8th IEEE Workshop on Neural Networks for Signal Processing VIII, Cambridge, Engl.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Young, PC , Tych, W & Pedregal, DJ 1998, 'Stochastic unobserved component models for adaptive signal extraction and forecasting', Paper presented at Proceedings of the 1998 8th IEEE Workshop on Neural Networks for Signal Processing VIII, Cambridge, Engl, 31/08/98 - 2/09/98 pp. 234-243.

APA

Young, P. C., Tych, W., & Pedregal, D. J. (1998). Stochastic unobserved component models for adaptive signal extraction and forecasting. 234-243. Paper presented at Proceedings of the 1998 8th IEEE Workshop on Neural Networks for Signal Processing VIII, Cambridge, Engl.

Vancouver

Young PC , Tych W, Pedregal DJ. Stochastic unobserved component models for adaptive signal extraction and forecasting. 1998. Paper presented at Proceedings of the 1998 8th IEEE Workshop on Neural Networks for Signal Processing VIII, Cambridge, Engl.

Author

Young, Peter C. ; Tych, Wlodek ; Pedregal, Diego J. / Stochastic unobserved component models for adaptive signal extraction and forecasting. Paper presented at Proceedings of the 1998 8th IEEE Workshop on Neural Networks for Signal Processing VIII, Cambridge, Engl.10 p.

Bibtex

@conference{c7c3c54d93d8427aa02f5c578a3dfdcd,

title = "Stochastic unobserved component models for adaptive signal extraction and forecasting",

abstract = "The adaptive, off-line signal processing and forecasting of nonstationary signals described by an unobserved component (UC) model is presented. The off-line signal processing based on a dynamic harmonic regression (DHR) model of the UC type and its performance via a typical problem of audio signal restoration are discussed. The simplest possible method of detecting outliers is used but more sophisticated approaches based on either their statistical properties of the KF innovations or the difference between the KF and FIS estimates are possible.",

author = "Young, {Peter C.} and Wlodek Tych and Pedregal, {Diego J.}",

year = "1998",

language = "English",

pages = "234--243",

note = "Proceedings of the 1998 8th IEEE Workshop on Neural Networks for Signal Processing VIII ; Conference date: 31-08-1998 Through 02-09-1998",

}

RIS

TY - CONF

T1 - Stochastic unobserved component models for adaptive signal extraction and forecasting

AU - Young, Peter C.

AU - Tych, Wlodek

AU - Pedregal, Diego J.

PY - 1998

Y1 - 1998

N2 - The adaptive, off-line signal processing and forecasting of nonstationary signals described by an unobserved component (UC) model is presented. The off-line signal processing based on a dynamic harmonic regression (DHR) model of the UC type and its performance via a typical problem of audio signal restoration are discussed. The simplest possible method of detecting outliers is used but more sophisticated approaches based on either their statistical properties of the KF innovations or the difference between the KF and FIS estimates are possible.

AB - The adaptive, off-line signal processing and forecasting of nonstationary signals described by an unobserved component (UC) model is presented. The off-line signal processing based on a dynamic harmonic regression (DHR) model of the UC type and its performance via a typical problem of audio signal restoration are discussed. The simplest possible method of detecting outliers is used but more sophisticated approaches based on either their statistical properties of the KF innovations or the difference between the KF and FIS estimates are possible.

UR - http://www.scopus.com/inward/record.url?scp=0031640660&partnerID=8YFLogxK

M3 - Conference paper

AN - SCOPUS:0031640660

SP - 234

EP - 243

T2 - Proceedings of the 1998 8th IEEE Workshop on Neural Networks for Signal Processing VIII

Y2 - 31 August 1998 through 2 September 1998

ER -

Research