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Electrocardiogram Signal Compression Using Beta Wavelets

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Journal of Mathematical Modelling and Algorithms

Abstract

In this paper, a wavelet based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs new wavelet filters whose coefficients are derived with beta function and its derivatives. A comparative study of performance of different existing wavelet filters and the Beta wavelet filters is made in terms of compression ratio (CR), percent root mean square difference (PRD), mean square error (MSE) and signal-to-noise ratio (SNR). When compared, the Beta wavelet filters give better compression ratio and also yields good fidelity parameters as compared to other wavelet filters. The simulation result included in this paper shows the clearly increased efficacy and performance in the field of biomedical signal processing.

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Authors and Affiliations

  1. PDPM Indian Institute of Information Technology Design and Manufacturing, Jabalpur, 482005, MP, India

    Ranjeet Kumar, Anil Kumar & Rajesh Kumar Pandey

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  1. Ranjeet Kumar
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  2. Anil Kumar
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  3. Rajesh Kumar Pandey
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Correspondence to Anil Kumar.

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Kumar, R., Kumar, A. & Pandey, R.K. Electrocardiogram Signal Compression Using Beta Wavelets. J Math Model Algor 11, 235–248 (2012). https://doi.org/10.1007/s10852-012-9181-9

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  • DOI: https://doi.org/10.1007/s10852-012-9181-9

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