Computing the Fourier Transformation over Temporal Data Streams (Invited Talk)

Authors Michael H. Böhlen , Muhammad Saad



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Author Details

Michael H. Böhlen
  • University of Zürich, Switzerland
Muhammad Saad
  • University of Zürich, Switzerland

Cite AsGet BibTex

Michael H. Böhlen and Muhammad Saad. Computing the Fourier Transformation over Temporal Data Streams (Invited Talk). In 26th International Symposium on Temporal Representation and Reasoning (TIME 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 147, pp. 1:1-1:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.TIME.2019.1

Abstract

In radio astronomy the sky is continuously scanned to collect frequency information about celestial objects. The inverse 2D Fourier transformation is used to generate images of the sky from the collected frequency information. We propose an algorithm that incrementally refines images by processing frequency information as it arrives in a temporal data stream. A direct implementation of the refinement with the discrete Fourier transformation requires O(N^2) complex multiplications to process an element of the stream. We propose a new algorithm that avoids recomputations and only requires O(N) complex multiplications.

Subject Classification

ACM Subject Classification
  • Information systems → Stream management
  • Theory of computation → Data structures and algorithms for data management
Keywords
  • Data streams
  • Fourier transform
  • time-varying data

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References

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