A REVIEW OF FLICKER-NOISE SPECTROSCOPY: INFORMATION IN CHAOTIC SIGNALS

Serge F. Timashev, Yuriy S. Polyakov

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

Flicker-Noise Spectroscopy (FNS), a general approach to the extraction and parameterization of resonant and stochastic components contained in medical time series, is presented. The basic idea of FNS is to treat as main information carriers the correlation links present in sequences of different irregularities, such as spikes, “jumps”, and discontinuities in derivatives of different orders, on all levels of the spatiotemporal hierarchy of the system under study. The tools for extracting and analyzing the information are power spectra and difference moments (structural functions), which complement each other’s information. The stochastic component derived from the structural function is formed exclusively by “jumps” of the dynamic variable while the stochastic component derived from the power spectrum is formed by both spikes and “jumps” on every level of the hierarchy. An application of this approach to the analysis of electroencephalogram signals is discussed.

Original languageEnglish (US)
Title of host publicationSimultaneity
Subtitle of host publicationTemporal Structures and Observer Perspectives
PublisherWorld Scientific Publishing Co.
Pages270-285
Number of pages16
ISBN (Electronic)9789812792426
ISBN (Print)9789812792419
DOIs
StatePublished - Jan 1 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Mathematics

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