Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

The VIT Transform Approach to Discrete-Time Signals and Linear Time-Varying Systems

Version 1 : Received: 24 January 2021 / Approved: 25 January 2021 / Online: 25 January 2021 (14:50:14 CET)

How to cite: Kamen, E. The VIT Transform Approach to Discrete-Time Signals and Linear Time-Varying Systems. Preprints 2021, 2021010504 (doi: 10.20944/preprints202101.0504.v1). Kamen, E. The VIT Transform Approach to Discrete-Time Signals and Linear Time-Varying Systems. Preprints 2021, 2021010504 (doi: 10.20944/preprints202101.0504.v1).

Abstract

A transform approach based on a variable initial time (VIT) formulation is developed for discrete-time signals and linear time-varying discrete-time systems or digital filters. The VIT transform is a formal power series in z^(-1) which converts functions given by linear time-varying difference equations into left polynomial fractions with variable coefficients, and with initial conditions incorporated into the framework. It is shown that the transform satisfies a number of properties that are analogous to those of the ordinary z-transform, and that it is possible to do scaling of z^(- i) by time functions which results in left-fraction forms for the transform of a large class of functions including sinusoids with general time-varying amplitudes and frequencies. Using the extended right Euclidean algorithm in a skew polynomial ring with time-varying coefficients, it is shown that a sum of left polynomial fractions can be written as a single fraction, which results in linear time-varying recursions for the inverse transform of the combined fraction. The extraction of a first-order term from a given polynomial fraction is carried out in terms of the evaluation of z^(i) at time functions. In the application to linear time-varying systems, it is proved that the VIT transform of the system output is equal to the product of the VIT transform of the input and the VIT transform of the unit-pulse response function. For systems given by a time-varying moving average or an autoregressive model, the transform framework is used to determine the steady-state output response resulting from various signal inputs such as the step and cosine functions.

Subject Areas

z-transform; time-varying systems; time-varying difference equations; skew polynomial rings; extended Euclidean algorithm; fraction decomposition

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