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Discrete LS Estimates of Correlation Function of Bi-Periodically Correlated Random Signals

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Abstract

Analysis of discrete estimates of bi-periodically correlated random processes (BPCRP)—mathematical models of signals with double stochastic periodicity was performed using least squares (LS) technique. It is shown that LS utilization allows to avoid systematic errors related to leakage effect. Expressions for estimate bias and dispersion were obtained, allowing determination systematic and mean square errors depending on discretization step, sample number and signal parameters were obtained. For quadrature BPCRP model discrete and continuous dispersions of LS estimation of correlation components were compared. Recommendations for discretization step are given.

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Authors and Affiliations

  1. Karpenko Physico-Mechanical Institute of NASU, Lviv, Ukraine

    Ihor N. Yavorskyj, Oksana Yu. Dzeryn & Roman Yuzefovych

  2. University of Technology and Life Sciences, Bydgoszcz, Poland

    Ihor N. Yavorskyj

  3. Lviv Polytechnic National University, Lviv, Ukraine

    Roman Yuzefovych

Authors
  1. Ihor N. Yavorskyj
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  2. Oksana Yu. Dzeryn
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  3. Roman Yuzefovych
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Correspondence to Ihor N. Yavorskyj or Roman Yuzefovych.

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I. N. Yavorskyj, O. Yu. Dzeryn, and R. Yuzefovych

The authors declare that they have no conflict of interest.

The initial version of this paper in Russian is published in the journal “Izvestiya Vysshikh Uchebnykh Zavedenii. Radioelektronika,” ISSN 2307-6011 (Online), ISSN 0021-3470 (Print) on the link http://radio.kpi.ua/article/view/S0021347020030036 with DOI: https://doi.org/10.20535/S0021347020030036

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Yavorskyj, I.N., Dzeryn, O.Y. & Yuzefovych, R. Discrete LS Estimates of Correlation Function of Bi-Periodically Correlated Random Signals. Radioelectron.Commun.Syst. 63, 136–155 (2020). https://doi.org/10.3103/S0735272720030036

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  • DOI: https://doi.org/10.3103/S0735272720030036

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