An improved method for blind separation of complex-valued signals via joint diagonalization

Xian-Feng Xu; Da-Zheng Feng; Wei Xing Zheng

doi:10.1109/ISCAS.2011.5937646

An improved method for blind separation of complex-valued signals via joint diagonalization

Xian-Feng Xu, Da-Zheng Feng, Wei Xing Zheng

School of Computer, Data & Mathematical Sciences

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

Abstract

The problem of blind separation of complex-valued signals via joint diagonalization of a set of non-unitary target matrices is addressed in this paper. An improved blind source separation (BSS) algorithm is developed based on minimization of the Frobenius-norm formulation of the approximate joint diagonalization problem by using a multiplicative update. Such minimization yields a strictly diagonally-dominant updated matrix at each iteration. With relaxing some constraints on the target matrices, the improved BSS algorithm allows for extended applications. The behavior of the improved BSS algorithm is demonstrated by computer simulation results in comparison with some representative BSS algorithms.

Original language	English
Title of host publication	Proceedings of the 2011 IEEE International Symposium on Circuits and Systems (ISCAS 2011), Rio de Janeiro, Brazil, 15-18 May 2011
Publisher	IEEE
Pages	637-640
Number of pages	4
ISBN (Print)	9781424494736
DOIs	https://doi.org/10.1109/ISCAS.2011.5937646
Publication status	Published - 2011
Event	IEEE International Symposium on Circuits and Systems - Duration: 20 May 2012 → …

Conference

Conference	IEEE International Symposium on Circuits and Systems
Period	20/05/12 → …

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10.1109/ISCAS.2011.5937646

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title = "An improved method for blind separation of complex-valued signals via joint diagonalization",

abstract = "The problem of blind separation of complex-valued signals via joint diagonalization of a set of non-unitary target matrices is addressed in this paper. An improved blind source separation (BSS) algorithm is developed based on minimization of the Frobenius-norm formulation of the approximate joint diagonalization problem by using a multiplicative update. Such minimization yields a strictly diagonally-dominant updated matrix at each iteration. With relaxing some constraints on the target matrices, the improved BSS algorithm allows for extended applications. The behavior of the improved BSS algorithm is demonstrated by computer simulation results in comparison with some representative BSS algorithms.",

author = "Xian-Feng Xu and Da-Zheng Feng and Zheng, {Wei Xing}",

year = "2011",

doi = "10.1109/ISCAS.2011.5937646",

language = "English",

isbn = "9781424494736",

pages = "637--640",

booktitle = "Proceedings of the 2011 IEEE International Symposium on Circuits and Systems (ISCAS 2011), Rio de Janeiro, Brazil, 15-18 May 2011",

publisher = "IEEE",

note = "IEEE International Symposium on Circuits and Systems ; Conference date: 20-05-2012",

}

Xu, X-F, Feng, D-Z & Zheng, WX 2011, An improved method for blind separation of complex-valued signals via joint diagonalization. in Proceedings of the 2011 IEEE International Symposium on Circuits and Systems (ISCAS 2011), Rio de Janeiro, Brazil, 15-18 May 2011. IEEE, pp. 637-640, IEEE International Symposium on Circuits and Systems, 20/05/12. https://doi.org/10.1109/ISCAS.2011.5937646

An improved method for blind separation of complex-valued signals via joint diagonalization. / Xu, Xian-Feng; Feng, Da-Zheng; Zheng, Wei Xing.
Proceedings of the 2011 IEEE International Symposium on Circuits and Systems (ISCAS 2011), Rio de Janeiro, Brazil, 15-18 May 2011. IEEE, 2011. p. 637-640.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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N2 - The problem of blind separation of complex-valued signals via joint diagonalization of a set of non-unitary target matrices is addressed in this paper. An improved blind source separation (BSS) algorithm is developed based on minimization of the Frobenius-norm formulation of the approximate joint diagonalization problem by using a multiplicative update. Such minimization yields a strictly diagonally-dominant updated matrix at each iteration. With relaxing some constraints on the target matrices, the improved BSS algorithm allows for extended applications. The behavior of the improved BSS algorithm is demonstrated by computer simulation results in comparison with some representative BSS algorithms.

AB - The problem of blind separation of complex-valued signals via joint diagonalization of a set of non-unitary target matrices is addressed in this paper. An improved blind source separation (BSS) algorithm is developed based on minimization of the Frobenius-norm formulation of the approximate joint diagonalization problem by using a multiplicative update. Such minimization yields a strictly diagonally-dominant updated matrix at each iteration. With relaxing some constraints on the target matrices, the improved BSS algorithm allows for extended applications. The behavior of the improved BSS algorithm is demonstrated by computer simulation results in comparison with some representative BSS algorithms.

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PB - IEEE

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Y2 - 20 May 2012

ER -

An improved method for blind separation of complex-valued signals via joint diagonalization

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