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On Locally Dyadic Stationary Processes

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>08/2017
<mark>Journal</mark>IEEE Transactions on Information Theory
Issue number8
Volume63
Number of pages9
Pages (from-to)4829-4837
Publication statusPublished
Early online date21/11/16
Original languageEnglish

Abstract

We introduce the concept of local dyadic stationarity, to account for nonstationary time series, within the framework of Walsh-Fourier analysis. We define and study time-varying, dyadic, autoregressive, moving average (tvDARMA) models. It is proven that the general tvDARMA process can be approximated locally by either a time-varying dyadic moving average and a time-varying dyadic autoregressive processes.