Fractional Power Spectra in Diagnostics of controlled Anishchenko-Astakhov System

The article is devoted to the consideration of the diagnostics of the controlled discrete-nonlinear Anishchenko-Astakhov system by the fractional-power spectra of the signals generated by the system. The conditions for the closeness of the system of fractional power-law functions of time, which redu...

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Veröffentlicht in:2021 Systems of Signals Generating and Processing in the Field of on Board Communications S. 1 - 6
Hauptverfasser: Loginov, S.S., Afanasiev, V. V.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 16.03.2021
Schlagworte:
Anishchenko-Astakhov system
Chaos
Control systems
Correlation
diagnostics
fractional power spectrum
Modulation
Process control
Signal representation
Spectral analysis
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Zusammenfassung:The article is devoted to the consideration of the diagnostics of the controlled discrete-nonlinear Anishchenko-Astakhov system by the fractional-power spectra of the signals generated by the system. The conditions for the closeness of the system of fractional power-law functions of time, which reduce the errors in the representation of signals of discrete-nonlinear systems by fractional power series, are determined. The peculiarities of the representation of the signals of the discrete-nonlinear Anishchenko-Astakhov system by pulse sequences with expansion in fractional powers of time are revealed, its adequacy in the analysis of system signals is confirmed. Two-dimensional and three-dimensional fractional-power spectra of the signals of the discrete-nonlinear Anishchenko-Astakhov system have been constructed. The ranges of variation of indicators of fractional powers and normalized pulse durations have been determined. The dependence of the structure of fractional power-law spectra of signals of a controlled discrete-nonlinear Anishchenko-Astakhov system, modified by modulation of time sampling parameters, on the modulation depth of control actions, which reduce the correlation intervals of the generated pseudo-random signals, is revealed.
DOI:10.1109/IEEECONF51389.2021.9416030