A Euclidean Direction based algorithm for blind source separation using a natural gradient

Glen W. Mabey; Jacob Gunther; Tamal Bose

A Euclidean Direction based algorithm for blind source separation using a natural gradient

Glen W. Mabey, Jacob Gunther, Tamal Bose

Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

The development in this paper is a extension of the adaptive RLS-type algorithm proposed by Zhu and Zhang. Their work uses the matrix inversion lemma to iteratively solve the equation obtained from the natural gradient of the nonlinear principle component analysis problem. This paper reduces the complexity of the solution by applying the Euclidean Direction Search concept in place of the matrix inversion lemma. The simulations performed show that the convergence rate is comparable, albeit slower, but with reduced complexity per iteration.

Original language	English (US)
Pages (from-to)	V-561-V-564
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	5
State	Published - 2004
Event	Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada Duration: May 17 2004 → May 21 2004

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "A Euclidean Direction based algorithm for blind source separation using a natural gradient",

abstract = "The development in this paper is a extension of the adaptive RLS-type algorithm proposed by Zhu and Zhang. Their work uses the matrix inversion lemma to iteratively solve the equation obtained from the natural gradient of the nonlinear principle component analysis problem. This paper reduces the complexity of the solution by applying the Euclidean Direction Search concept in place of the matrix inversion lemma. The simulations performed show that the convergence rate is comparable, albeit slower, but with reduced complexity per iteration.",

author = "Mabey, {Glen W.} and Jacob Gunther and Tamal Bose",

year = "2004",

language = "English (US)",

volume = "5",

pages = "V--561--V--564",

journal = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

issn = "1520-6149",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing ; Conference date: 17-05-2004 Through 21-05-2004",

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T1 - A Euclidean Direction based algorithm for blind source separation using a natural gradient

AU - Mabey, Glen W.

AU - Gunther, Jacob

AU - Bose, Tamal

PY - 2004

Y1 - 2004

N2 - The development in this paper is a extension of the adaptive RLS-type algorithm proposed by Zhu and Zhang. Their work uses the matrix inversion lemma to iteratively solve the equation obtained from the natural gradient of the nonlinear principle component analysis problem. This paper reduces the complexity of the solution by applying the Euclidean Direction Search concept in place of the matrix inversion lemma. The simulations performed show that the convergence rate is comparable, albeit slower, but with reduced complexity per iteration.

AB - The development in this paper is a extension of the adaptive RLS-type algorithm proposed by Zhu and Zhang. Their work uses the matrix inversion lemma to iteratively solve the equation obtained from the natural gradient of the nonlinear principle component analysis problem. This paper reduces the complexity of the solution by applying the Euclidean Direction Search concept in place of the matrix inversion lemma. The simulations performed show that the convergence rate is comparable, albeit slower, but with reduced complexity per iteration.

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M3 - Conference article

SN - 1520-6149

VL - 5

SP - V-561-V-564

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 17 May 2004 through 21 May 2004

ER -

A Euclidean Direction based algorithm for blind source separation using a natural gradient

Abstract

ASJC Scopus subject areas

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