Comparison of low rank tensorial approximation to discrete wavelet approximation of given nonstationary time series

Authors

  • Dato DATUASHVILI International Black Sea University
  • Cihan MERT International Black Sea University

DOI:

https://doi.org/10.31578/.v4i1.70

Keywords:

DWT (discrete wavelet transform), SSA (singular spectrum analysis), Low Rank Tensorial approximation, Hankel data matrix, SNR (signal to noise ratio)

Abstract

Approximation and filtration of time series belongs to one of most important problems in real word scientific application. Despite of plenty of
existed methods, they are effective in very specific situations, most of them assume that time series is stationary or can be stationary by finite
amount of differencing. In this article we will consider several time series and compare Singular spectrum analysis and its low rank tensorial
approximation method to classical wavelet decomposition approach.

Author Biographies

Dato DATUASHVILI, International Black Sea University

Study process Administrator, Faculty of Computer Technology and Engineering

Cihan MERT, International Black Sea University

Assoc.Prof.Dr .Dean. , Faculty of Computer Technology and Engineering

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Published

31-05-2015

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Section

Articles