ANALYSIS OF DISCRETE SIGNALS WITH STOCHASTIC COMPONENTS USING FLICKER NOISE SPECTROSCOPY
| Autor: | Serge F. Timashev, Yuriy Polyakov |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Series (mathematics)
Heaviside step function Computer science Applied Mathematics FOS: Physical sciences Spectral density Probability and statistics Physics - Medical Physics Signal Moment (mathematics) symbols.namesake Sampling (signal processing) Physics - Data Analysis Statistics and Probability Modeling and Simulation symbols Flicker noise Medical Physics (physics.med-ph) Engineering (miscellaneous) Algorithm Data Analysis Statistics and Probability (physics.data-an) |
| Zdroj: | International Journal of Bifurcation and Chaos. 18:2793-2797 |
| ISSN: | 1793-6551 0218-1274 |
| DOI: | 10.1142/s0218127408022020 |
| Popis: | 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 and Heaviside 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. Comment: 6 pages, 3 figures |
| Databáze: | OpenAIRE |
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