The Discrete Orthogonal Stockwell Transforms For Infinite-Length Signals And Their Real-Time Implementations

Yusong Yan, Hongmei Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent literature, the discrete Stockwell Transform (DST) for infinite length signals has been introduced along with its fast implementation. This method allows for low computational cost and enables processing of an infinite-length or large-size signal segment-by-segment while overcoming the boundary effects produced by conventional DST. The algorithm also preserves the absolute-reference phase, making it suitable for real-time signal processing. In this paper, we propose a new formulation of the discrete Orthogonal Stockwell Transform for infinite length signals. Based on the definition, we implement its fast algorithm using FFT. Our proposed scheme can process an infinite signal segment-by-segment, eliminating boundary effects and preserving the absolute-reference phase. Compared to the DST for infinite length signals, the DOST version significantly reduces computational complexity, making it more practical for real-time signal processing.

Original languageEnglish
Title of host publication31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages1773-1777
Number of pages5
ISBN (Electronic)9789464593600
DOIs
Publication statusPublished - 2023
Event31st European Signal Processing Conference, EUSIPCO 2023 - Helsinki, Finland
Duration: 4 Sept 20238 Sept 2023

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491

Conference

Conference31st European Signal Processing Conference, EUSIPCO 2023
Country/TerritoryFinland
CityHelsinki
Period4/09/238/09/23

Keywords

  • Infinite-length signals
  • real-time signal processing
  • the discrete Orthogonal Stockwell transforms
  • the discrete Stockwell transforms

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