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Near-Ideal Predictors and Causal Filters for Discrete-Time Signals

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Abstract

The paper presents linear predictors and causal filters for discrete-time signals featuring some different kinds of spectrum degeneracy. These predictors and filters are based on approximation of ideal noncausal transfer functions by causal transfer functions represented by polynomials of the Z-transform of the unit step signal.

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Funding

This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.

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Authors and Affiliations

  1. ZJU-UIUC (Zhejiang University / University of Illinois at Urbana-Champaign) Institute, Zhejiang University, Haining, Zhejiang Province, China

    N. G. Dokuchaev

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  1. N. G. Dokuchaev
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Correspondence to N. G. Dokuchaev.

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Additional information

Translated from Problemy Peredachi Informatsii, 2023, Vol. 59, No. 2, pp. 32–48. https://doi.org/10.31857/S0555292323020031

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Dokuchaev, N.G. Near-Ideal Predictors and Causal Filters for Discrete-Time Signals. Probl Inf Transm 59, 99–114 (2023). https://doi.org/10.1134/S0032946023020035

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