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Sequential Extraction Algorithm for BSS Without Error Accumulation

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

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Abstract

Blind source separation (BSS) is an emerging research field in both theory and applications. In this paper we propose a kurtosis maximization algorithm–Sequential Extraction Algorithm, which can extract the source signals sequentially. This approach is based on an algorithm for separating one signal (Algorithm 1) and some technique to eliminate the accumulating errors, which often occur in the sequential extraction steps. In Algorithm 1, a new criterion to judge whether the separated signal is an original source signal, is proposed. In Sequential Extraction Algorithm, we propose a new approach to eliminate accumulating errors, which is caused in the sequential extraction process. This approach is based on the cost function involved in this algorithm, and thus, is different from those available in literature.

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Liu, Q., Chen, T. (2005). Sequential Extraction Algorithm for BSS Without Error Accumulation. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_76

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  • DOI: https://doi.org/10.1007/11427445_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25913-8

  • Online ISBN: 978-3-540-32067-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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