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Hybrid Fractal-Wavelet Method for Multi-Channel EEG Signal Compression

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Abstract

In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. First, an effective decorrelation is performed through the principal component analysis of different channels to efficiently compress the multi-channel EEG data. Then, the decorrelated EEG signal is decomposed using wavelet packet transform (WPT). Finally, fractal encoding is applied to the low frequency coefficients of WPT, and a modified wavelet-based coding is used for coding the remaining high frequency coefficients. This new method provides improved compression results as compared to the wavelet and fractal compression methods.

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Acknowledgments

The valuable comments of the anonymous reviewers obviously contributed to the improvement of this paper.

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Authors and Affiliations

  1. Electrical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), 424, Hafez Ave., Tehran, Iran

    Jamal Saeedi & Karim Faez

  2. Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), 424, Hafez Ave., Tehran, Iran

    Mohammad Hassan Moradi

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  1. Jamal Saeedi
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  2. Karim Faez
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  3. Mohammad Hassan Moradi
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Correspondence to Jamal Saeedi.

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Saeedi, J., Faez, K. & Moradi, M.H. Hybrid Fractal-Wavelet Method for Multi-Channel EEG Signal Compression. Circuits Syst Signal Process 33, 2583–2604 (2014). https://doi.org/10.1007/s00034-014-9764-y

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  • DOI: https://doi.org/10.1007/s00034-014-9764-y

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