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Near-Ideal Predictors and Causal Filters for Discrete-Time Signals
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Journal Article
Near-Ideal Predictors and Causal Filters for Discrete-Time Signals
2023
Overview
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.
Publisher
Pleiades Publishing,Springer Nature B.V
Subject
