Independent component analysis with feature selective filtering

Yi Ou Li; Tülay Adali; Vince D. Calhoun

Independent component analysis with feature selective filtering

Yi Ou Li, Tülay Adali, Vince D. Calhoun

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

Abstract

In this contribution, we propose a feature selective filtering scheme for independent component analysis (ICA) to improve the estimation of the sources of interest (SOI), i.e., sources that have certain desired features in their sample space. As an example, we show that ICA with a smooth filtering scheme can improve the estimation of the smooth image sources from a mixture of images, as well as the estimation of a smooth visual activation map in a hybrid functional magnetic resonance imaging (fMRI) data set. Hence, the technique can potentially be used in the analysis of fMRI data to improve the ICA estimation of functional activation regions that are expected to be smooth.

Original language	English (US)
Title of host publication	Machine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop
Editors	A. Barros, J. Principe, J. Larsen, T. Adali, S. Douglas
Pages	193-202
Number of pages	10
State	Published - Dec 1 2004
Externally published	Yes
Event	Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop - Sao Luis, Brazil Duration: Sep 29 2004 → Oct 1 2004

Publication series

Name	Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop

Other

Other	Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop
Country/Territory	Brazil
City	Sao Luis
Period	9/29/04 → 10/1/04

ASJC Scopus subject areas

Engineering(all)

Cite this

Li, Y. O., Adali, T., & Calhoun, V. D. (2004). Independent component analysis with feature selective filtering. In A. Barros, J. Principe, J. Larsen, T. Adali, & S. Douglas (Eds.), Machine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop (pp. 193-202). (Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop).

Independent component analysis with feature selective filtering. / Li, Yi Ou; Adali, Tülay; Calhoun, Vince D.

Machine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop. ed. / A. Barros; J. Principe; J. Larsen; T. Adali; S. Douglas. 2004. p. 193-202 (Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop).

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

Li, YO, Adali, T & Calhoun, VD 2004, Independent component analysis with feature selective filtering. in A Barros, J Principe, J Larsen, T Adali & S Douglas (eds), Machine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop. Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop, pp. 193-202, Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop, Sao Luis, Brazil, 9/29/04.

Li YO, Adali T, Calhoun VD. Independent component analysis with feature selective filtering. In Barros A, Principe J, Larsen J, Adali T, Douglas S, editors, Machine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop. 2004. p. 193-202. (Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop).

Li, Yi Ou ; Adali, Tülay ; Calhoun, Vince D. / Independent component analysis with feature selective filtering. Machine Learning for Signal Processing XIV - Proceedings of 2004 IEEE Signal Processing Society Workshop. editor / A. Barros ; J. Principe ; J. Larsen ; T. Adali ; S. Douglas. 2004. pp. 193-202 (Machine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop).

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Independent component analysis with feature selective filtering

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