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On the Relationships Between Power Iteration, Inverse Iteration and FastICA

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Independent Component Analysis and Signal Separation (ICA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4666))

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Abstract

In recent years, there has been an increasing interest in developing new algorithms for digital signal processing by applying and generalising existing numerical linear algebra tools. A recent result shows that the FastICA algorithm, a popular state-of-the-art method for linear Independent Component Analysis (ICA), shares a nice interpretation as a Newton type method with the Rayleigh Quotient Iteration (RQI), the latter method wellknown to the numerical linear algebra community. In this work, we develop an analogous theory of single vector iteration ICA methods. Two classes of methods are proposed for the one-unit linear ICA problem, namely, power ICA methods and inverse iteration ICA methods. By means of a scalar shift, scalar shifted versions of both power ICA method and inverse iteration ICA method are proposed and proven to be locally quadratically convergent to a correct demixing vector.

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References

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Mike E. Davies Christopher J. James Samer A. Abdallah Mark D Plumbley

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© 2007 Springer-Verlag Berlin Heidelberg

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Shen, H., Hüper, K. (2007). On the Relationships Between Power Iteration, Inverse Iteration and FastICA. In: Davies, M.E., James, C.J., Abdallah, S.A., Plumbley, M.D. (eds) Independent Component Analysis and Signal Separation. ICA 2007. Lecture Notes in Computer Science, vol 4666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74494-8_14

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  • DOI: https://doi.org/10.1007/978-3-540-74494-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74493-1

  • Online ISBN: 978-3-540-74494-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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