Dual auto-regressive modelling approach to Gaussian process identification

Yiu Ming CHEUNG*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-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 languageEnglish
Title of host publicationProceedings - IEEE International Conference on Multimedia and Expo
PublisherIEEE Computer Society
Pages1053-1056
Number of pages4
ISBN (Electronic)0769511988
DOIs
Publication statusPublished - 2001
Event2001 IEEE International Conference on Multimedia and Expo, ICME 2001 - Tokyo, Japan
Duration: 22 Aug 200125 Aug 2001

Publication series

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

Conference

Conference2001 IEEE International Conference on Multimedia and Expo, ICME 2001
Country/TerritoryJapan
CityTokyo
Period22/08/0125/08/01

Scopus Subject Areas

  • Computer Networks and Communications
  • Computer Science Applications

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