Dual auto-regressive modelling approach to Gaussian process identification

Yiu Ming Cheung

doi:10.1109/ICME.2001.1237906

Dual auto-regressive modelling approach to Gaussian process identification

Yiu Ming Cheung^*

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

5 Citations (Scopus)

Abstract

By modelling sources as a multivariate auto-regressive (AR) process, we have recently presented a dual AR modelling approach to identify temporal sources in independent component analysis (ICA) (Cheung et al. 2000, Cheung and Xu 1999 & 2001). However, our proposed existing algorithms for this approach are only suitable for the case that the residual term of the AR source process is non-Gaussian white noise. In this paper, we further study the Gaussian case, whereby a maximum-likelihood based algorithm is presented and experimentally demonstrated.

Original language	English
Title of host publication	Proceedings - IEEE International Conference on Multimedia and Expo
Publisher	IEEE Computer Society
Pages	1053-1056
Number of pages	4
ISBN (Electronic)	0769511988
DOIs	https://doi.org/10.1109/ICME.2001.1237906
Publication status	Published - 2001
Event	2001 IEEE International Conference on Multimedia and Expo, ICME 2001 - Tokyo, Japan Duration: 22 Aug 2001 → 25 Aug 2001

Publication series

Name	Proceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)	1945-7871
ISSN (Electronic)	1945-788X

Conference

Conference	2001 IEEE International Conference on Multimedia and Expo, ICME 2001
Country/Territory	Japan
City	Tokyo
Period	22/08/01 → 25/08/01

Scopus Subject Areas

Computer Networks and Communications
Computer Science Applications

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10.1109/ICME.2001.1237906

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title = "Dual auto-regressive modelling approach to Gaussian process identification",

abstract = "By modelling sources as a multivariate auto-regressive (AR) process, we have recently presented a dual AR modelling approach to identify temporal sources in independent component analysis (ICA) (Cheung et al. 2000, Cheung and Xu 1999 & 2001). However, our proposed existing algorithms for this approach are only suitable for the case that the residual term of the AR source process is non-Gaussian white noise. In this paper, we further study the Gaussian case, whereby a maximum-likelihood based algorithm is presented and experimentally demonstrated.",

author = "Cheung, {Yiu Ming}",

year = "2001",

doi = "10.1109/ICME.2001.1237906",

language = "English",

series = "Proceedings - IEEE International Conference on Multimedia and Expo",

publisher = "IEEE Computer Society",

pages = "1053--1056",

booktitle = "Proceedings - IEEE International Conference on Multimedia and Expo",

address = "United States",

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Cheung, YM 2001, Dual auto-regressive modelling approach to Gaussian process identification. in Proceedings - IEEE International Conference on Multimedia and Expo., 1237906, Proceedings - IEEE International Conference on Multimedia and Expo, IEEE Computer Society, pp. 1053-1056, 2001 IEEE International Conference on Multimedia and Expo, ICME 2001, Tokyo, Japan, 22/08/01. https://doi.org/10.1109/ICME.2001.1237906

Dual auto-regressive modelling approach to Gaussian process identification. / Cheung, Yiu Ming.
Proceedings - IEEE International Conference on Multimedia and Expo. IEEE Computer Society, 2001. p. 1053-1056 1237906 (Proceedings - IEEE International Conference on Multimedia and Expo).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AB - By modelling sources as a multivariate auto-regressive (AR) process, we have recently presented a dual AR modelling approach to identify temporal sources in independent component analysis (ICA) (Cheung et al. 2000, Cheung and Xu 1999 & 2001). However, our proposed existing algorithms for this approach are only suitable for the case that the residual term of the AR source process is non-Gaussian white noise. In this paper, we further study the Gaussian case, whereby a maximum-likelihood based algorithm is presented and experimentally demonstrated.

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T3 - Proceedings - IEEE International Conference on Multimedia and Expo

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BT - Proceedings - IEEE International Conference on Multimedia and Expo

PB - IEEE Computer Society

T2 - 2001 IEEE International Conference on Multimedia and Expo, ICME 2001

Y2 - 22 August 2001 through 25 August 2001

ER -

Dual auto-regressive modelling approach to Gaussian process identification

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