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Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain

Email: miguel.sanjuan@urjc.es

Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email: aluo@siue.edu


Fluctuation Metrology Based on the Prony's Spectroscopy (II)

Journal of Applied Nonlinear Dynamics 1(3) (2012) 207--226 | DOI:10.5890/JAND.2012.06.001

Raoul R. Nigmatullin

Theoretical Physics Department, Institute of Physics, Kazan Federal University, Kremlevskaya str., 18, 420008, Kazan, Russian Federation

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Abstract

The basic purpose of this paper is related to creation of the basis of new metrology based on quantitative analysis of the Prony’s spectra. The Prony’s spectroscopy gives a possibility to transform a wide class of multi-periodic and random signals (associated with a clearly expressed trend) to their amplitudefrequency response (AFR). For the strongly-correlated complex systems with memory the corresponding AFR is generated by a few initial frequencies that allow realizing the further compression of the initial random signal and reading it in terms of the limited number of quantitative parameters. This important peculiarity of the Prony’s spectroscopy allows in creating of a “universal” language for reading of different fluctuations and comparing them with each other. One interesting example of reading of the infinite sequences that are formed from the transcendental numbers (the Euler’s constant E = 2.71828... and number π = 3.14159...) is considered. The new elements that are added to calculation scheme/algorithm increase the stability and accuracy of the Prony’s spectra considered. In general, it opens new possibilities in creation of the basis of the fluctuation metrology that enables to read a wide class of random signals and compare them with other signals in terms of the quantitative parameters entering into the corresponding AFRs that, in turn, are governed by the corresponding distribution of frequencies.

Acknowledgments

This paper was written in the frame of the scientific research program that was accepted by Kazan Federal University for 2012 year “Dielectric spectroscopy and kinetics of complex systems”.

References

  1. [1]  Timashev, S.F. and Polyakov, Yu. S. (2007), Review in Flicker-nose spectroscopy in electrochemistry, Fluctuation and Noise letters, 7, R15–R47.
  2. [2]  Nigmatullin, R.R., Osokin, S, I., and Toboev, V.A. (2011), NAFASS: Discrete spectroscopy of random signals, Chaos, Solitons and Fractals, 44, 226–240.
  3. [3]  Nigmatullin, R.R. (2012), Is it possible to replace the probability distribution function describing a random process by the , Prony’s spectrum? (I) Journal of Applied Nonlinear Dynamics, , 1, 173–194.
  4. [4]  Ciurea, M.L., Lazanu, S., Stavaracher, I., Lepadatu, A-M., Iancu V., Mitroi, M.R., Nigmatullin, R.R. and Baleanu, C.M. (2011), Stressed induced traps in multilayed structures, J. of Applied Phys., 109, 013717.
  5. [5]  Nigmatullin, R.R., Popov, I.I. and Baleanu, D. (2011), Predictions based on the cumulative curves: Basic principles and nontrivial example, Communications in Nonlinear Science and Numerical Simulation, 16, 895.
  6. [6]  Nigmatullin, R.R. (2010), Universal distribution function for the strongly-correlated fluctuations: general way for description of random sequences, Communications in Nonlinear Science and Numerical Simulation, 15, 637.