A fixed-point algorithm for blind separation of temporally correlated sources

Zhenwei Shi; Dan Zhang; Changshui Zhang

doi:10.1109/icme.2007.4284626

A fixed-point algorithm for blind separation of temporally correlated sources

Zhenwei Shi^*
, Dan Zhang
, Changshui Zhang

^*Corresponding author for this work

School of Astronautics

Tsinghua University

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

1 Scopus citations

Abstract

In this paper we develop a new method for blind separation of temporally correlated sources, possibly dependent signals from linear mixtures of them. The proposed algorithm is based on the mutual independency of the innovations of source signals instead of original signals. This algorithm takes into account both the temporal structure and the high-order statistics of source signals and in contrast to the most known blind separation algorithms only exploiting the second order statistics or the non-Gaussianity. In this framework, a fixed-point algorithm is introduced. The fixed-point algorithm is computationally very simple, converge fast, and does not need choose any learning step sizes. Extensive computer simulations with speech signals and images confirm the validity and high performance of the proposed algorithm.

Original language	English
Title of host publication	Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
Publisher	IEEE Computer Society
Pages	220-223
Number of pages	4
ISBN (Print)	1424410177, 9781424410170
DOIs	https://doi.org/10.1109/icme.2007.4284626
State	Published - 2007
Event	IEEE International Conference onMultimedia and Expo, ICME 2007 - Beijing, China Duration: 2 Jul 2007 → 5 Jul 2007

Publication series

Name	Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

Conference

Conference	IEEE International Conference onMultimedia and Expo, ICME 2007
Country/Territory	China
City	Beijing
Period	2/07/07 → 5/07/07

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10.1109/icme.2007.4284626

Cite this

Shi, Z., Zhang, D., & Zhang, C. (2007). A fixed-point algorithm for blind separation of temporally correlated sources. In Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007 (pp. 220-223). Article 4284626 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007). IEEE Computer Society. https://doi.org/10.1109/icme.2007.4284626

@inproceedings{7ec71eacc3e14cf6b66d8d75bc6e743a,

title = "A fixed-point algorithm for blind separation of temporally correlated sources",

abstract = "In this paper we develop a new method for blind separation of temporally correlated sources, possibly dependent signals from linear mixtures of them. The proposed algorithm is based on the mutual independency of the innovations of source signals instead of original signals. This algorithm takes into account both the temporal structure and the high-order statistics of source signals and in contrast to the most known blind separation algorithms only exploiting the second order statistics or the non-Gaussianity. In this framework, a fixed-point algorithm is introduced. The fixed-point algorithm is computationally very simple, converge fast, and does not need choose any learning step sizes. Extensive computer simulations with speech signals and images confirm the validity and high performance of the proposed algorithm.",

author = "Zhenwei Shi and Dan Zhang and Changshui Zhang",

year = "2007",

doi = "10.1109/icme.2007.4284626",

language = "英语",

isbn = "1424410177",

series = "Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007",

publisher = "IEEE Computer Society",

pages = "220--223",

booktitle = "Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007",

address = "美国",

note = "IEEE International Conference onMultimedia and Expo, ICME 2007 ; Conference date: 02-07-2007 Through 05-07-2007",

}

Shi, Z, Zhang, D & Zhang, C 2007, A fixed-point algorithm for blind separation of temporally correlated sources. in Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007., 4284626, Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007, IEEE Computer Society, pp. 220-223, IEEE International Conference onMultimedia and Expo, ICME 2007, Beijing, China, 2/07/07. https://doi.org/10.1109/icme.2007.4284626

A fixed-point algorithm for blind separation of temporally correlated sources. / Shi, Zhenwei; Zhang, Dan; Zhang, Changshui.
Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. IEEE Computer Society, 2007. p. 220-223 4284626 (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007).

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

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N2 - In this paper we develop a new method for blind separation of temporally correlated sources, possibly dependent signals from linear mixtures of them. The proposed algorithm is based on the mutual independency of the innovations of source signals instead of original signals. This algorithm takes into account both the temporal structure and the high-order statistics of source signals and in contrast to the most known blind separation algorithms only exploiting the second order statistics or the non-Gaussianity. In this framework, a fixed-point algorithm is introduced. The fixed-point algorithm is computationally very simple, converge fast, and does not need choose any learning step sizes. Extensive computer simulations with speech signals and images confirm the validity and high performance of the proposed algorithm.

AB - In this paper we develop a new method for blind separation of temporally correlated sources, possibly dependent signals from linear mixtures of them. The proposed algorithm is based on the mutual independency of the innovations of source signals instead of original signals. This algorithm takes into account both the temporal structure and the high-order statistics of source signals and in contrast to the most known blind separation algorithms only exploiting the second order statistics or the non-Gaussianity. In this framework, a fixed-point algorithm is introduced. The fixed-point algorithm is computationally very simple, converge fast, and does not need choose any learning step sizes. Extensive computer simulations with speech signals and images confirm the validity and high performance of the proposed algorithm.

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ER -

A fixed-point algorithm for blind separation of temporally correlated sources

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