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A New Signal Segmentation Approach Based on Singular Value Decomposition and Intelligent Savitzky-Golay Filter

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Artificial Intelligence and Signal Processing (AISP 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 427))

Abstract

Signal segmentation, dividing non-stationary signals into semi-stationary parts that each has rather equal statistical characteristics is necessary in many signal analysis approaches. In this article, a novel signal segmentation approach based on the modified singular value decomposition (SVD) and intelligent Savitzky-Golay filter is proposed. First, Savitzky-Golay filter is used to minimize the least-squares error in fitting a polynomial to frames of noisy data. There are two parameters in this filter adjusted by many trials. In this paper we propose to use new particle swarm optimization (NPSO) for appropriate selecting of these parameters. Then, we employ two approaches based on the modified SVD to attain the boundaries of each segment. The proposed methods are applied in the both comprehensive synthetic signal and real EEG data. The results of using the proposed methods compared with three well-known algorithms, demonstrate the superiority of the proposed method.

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Acknowledgment

The authors wish to thank Prof. Saeid Sanei for his so valuable and kind guidance.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

    Hamed Azami

  2. Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

    Morteza Saraf

  3. Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

    Karim Mohammadi

Authors
  1. Hamed Azami
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  2. Morteza Saraf
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  3. Karim Mohammadi
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Corresponding author

Correspondence to Hamed Azami .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Ali Movaghar

  2. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Mansour Jamzad

  3. Sharif University of Technology, Tehran, Iran

    Hossein Asadi

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© 2014 Springer International Publishing Switzerland

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Azami, H., Saraf, M., Mohammadi, K. (2014). A New Signal Segmentation Approach Based on Singular Value Decomposition and Intelligent Savitzky-Golay Filter. In: Movaghar, A., Jamzad, M., Asadi, H. (eds) Artificial Intelligence and Signal Processing. AISP 2013. Communications in Computer and Information Science, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-10849-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-10849-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10848-3

  • Online ISBN: 978-3-319-10849-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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