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Identification of Delays in AMUSE Algorithm for Blind Signal Separation of Financial Data

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Artificial Intelligence and Soft Computing (ICAISC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12416))

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Abstract

In this article, we present a method of selecting the number of delays in the AMUSE blind signal separation (BSS) algorithm. This enhancement of the AMUSE algorithm enables the separation of signals in case of generating models that include additive noise. The choice of the set of delays is based on a new measure of the collective signal variability. The presented solution is tested both on benchmark signals as well as on real financial time series.

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References

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Author information

Authors and Affiliations

  1. Warsaw School of Economics, Al. Niepodleglosci 162, 02-554, Warsaw, Poland

    Ryszard Szupiluk & Paweł Rubach

Authors
  1. Ryszard Szupiluk
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  2. Paweł Rubach
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Corresponding author

Correspondence to Paweł Rubach .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Szupiluk, R., Rubach, P. (2020). Identification of Delays in AMUSE Algorithm for Blind Signal Separation of Financial Data. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2020. Lecture Notes in Computer Science(), vol 12416. Springer, Cham. https://doi.org/10.1007/978-3-030-61534-5_23

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  • DOI: https://doi.org/10.1007/978-3-030-61534-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61533-8

  • Online ISBN: 978-3-030-61534-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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