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A robust method for parameter estimation of AR systems using empirical mode decomposition

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Abstract

This paper presents a robust algorithm for parameter estimation of autoregressive (AR) systems in noise using empirical mode decomposition (EMD) method. The basic idea is to represent the autocorrelation function of the noise-free AR signal as the summation of damped sinusoidal functions and use EMD for extracting these component functions as intrinsic mode functions (IMFs). Unlike conventional correlation-based techniques, the proposed scheme first estimates the damped sinusoidal model parameters from the IMFs of autocorrelation function using a least-squares based method. The AR parameters are then directly obtained from the extracted sinusoidal model parameters. Simulation results show that EMD is a very promising tool for AR system identification at a very low signal-to-noise ratio (SNR).

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh

    Md. Kamrul Hasan & M. Shakib Apu

  2. Department of Computer Science and Technology, Rajshahi University, Rajshahi, Bangladesh

    Md. Khademul Islam Molla

Authors
  1. Md. Kamrul Hasan
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  2. M. Shakib Apu
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  3. Md. Khademul Islam Molla
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Correspondence to Md. Kamrul Hasan.

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Hasan, M.K., Apu, M.S. & Molla, M.K.I. A robust method for parameter estimation of AR systems using empirical mode decomposition. SIViP 4, 451–461 (2010). https://doi.org/10.1007/s11760-009-0134-3

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  • DOI: https://doi.org/10.1007/s11760-009-0134-3

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