Analysis of discrete signals with stochastic components using flicker noise spectroscopy

Serge F. Timashev, Yuriy S. Polyakov

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

The problem of information extraction from discrete stochastic time series, produced with some finite sampling frequency, using flicker-noise spectroscopy, a general framework for information extraction based on the analysis of the correlation links between signal irregularities and formulated for continuous signals, is discussed. It is shown that the mathematical notions of Dirac δ- and Heaviside θ-functions used in the analysis of continuous signals may be interpreted as high-frequency and low-frequency stochastic components, respectively, in the case of discrete series. The analysis of electroencephalogram measurements for a teenager with schizophrenic symptoms at two different sampling frequencies demonstrates that the "power spectrum" and difference moment contain different information in the case of discrete signals, which was formally proven for continuous signals. The sampling interval itself is suggested as an additional parameter that should be included in general parameterization procedures for real signals.

Original languageEnglish (US)
Pages (from-to)2793-2797
Number of pages5
JournalInternational Journal of Bifurcation and Chaos
Volume18
Issue number9
DOIs
StatePublished - Sep 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Engineering (miscellaneous)
  • General
  • Applied Mathematics

Keywords

  • Discrete series
  • Power spectrum
  • Sampling interval
  • Structural function
  • Time series

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