Universal distribution function for the strongly-correlated fluctuations: General way for description of different random sequences

Abstract It has been proved that for the strongly-correlated fluctuations there is a universal distribution function for the relative fluctuations (UDFRF). The analytical form of this function follows from the solution of some types of the functional equations. For obtaining the UDFRF a procedure of the optimal linear smoothing (POLS) has been developed. This procedure based on criterion of the minimal relative error helps to separate correctly a possible trend (the “low-frequency” curve, defined as the generalized mean value curve or trend) from the “high-frequency” (HF) fluctuations, defined as a random sequence of relative fluctuations with zero trend. A universal treatment procedure outlined in this paper helps to find an optimal trend, separate it from the relative HF fluctuations and read them quantitatively . The statistics of the fractional moments outlined in this paper helps “to read” the found trends and express them in terms of the fitting parameters if the model for their description is absent . These new possibilities can be applied for description of different noises (quantum fluctuations, for example) that always present on the scale (10 −6  ÷ 10 −9  m). Quantitative reading of these noises with their subsequent classification is important for every developing nanotechnology that it has a possibility to be applied in this range of scales.

[1]  Raoul R. Nigmatullin,et al.  Dielectric relaxation in complex systems: quality sensing and dielectric properties of honeydew melons from 10 MHz to 1.8 GHz , 2006 .

[2]  S. Timashev A new dialogue with nature , 2000 .

[3]  Raoul R. Nigmatullin,et al.  Recognition of nonextensive statistical distributions by the eigencoordinates method , 2000 .

[4]  Alexey F. Bunkin,et al.  Detection of the OH band fine structure in liquid water by means of new treatment procedure based on the statistics of the fractional moments , 2007 .

[5]  D. Baleanu,et al.  Characterization of a benzoic acid modified glassy carbon electrode expressed quantitatively by new statistical parameters , 2009 .

[6]  R. Nigmatullin,et al.  Identification of a new function model for the AC-impedance of thermally evaporated undoped selenium films using the Eigen-coordinates method , 2001 .

[7]  Stochastic dynamics of time correlation in complex systems with discrete time , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[8]  Raoul R. Nigmatullin,et al.  Section 10. Dielectric methods, theory and simulation Is there geometrical/physical meaning of the fractional integral with complex exponent? , 2005 .

[9]  Raoul R. Nigmatullin,et al.  Strongly correlated variables and existence of a universal distribution function for relative fluctuations , 2008 .

[10]  R. Nigmatullin,et al.  Application of fractional-moments statistics to data for two-phase dielectric mixtures , 2008, IEEE transactions on dielectrics and electrical insulation.

[11]  P. Hänggi,et al.  Quantification of heart rate variability by discrete nonstationary non-Markov stochastic processes. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  R. Nigmatullin,et al.  New quantitative "reading" of dielectric spectra of complex biological systems , 2006, IEEE Transactions on Dielectrics and Electrical Insulation.

[13]  S. F. Timashev Self-similarity in nature , 2000 .

[14]  R. Yulmetyev,et al.  Intensity approximation of random fluctuation in complex systems , 2002 .

[15]  R. Nigmatullin Eigen-coordinates: New method of analytical functions identification in experimental measurements , 1998 .

[16]  Raoul R. Nigmatullin,et al.  The statistics of the fractional moments: Is there any chance to "read quantitatively" any randomness? , 2006, Signal Process..

[17]  R. Nigmatullin,et al.  The generalized mean value function approach: a new stastistical tool for the detection of weak signals in spectroscopy , 2005 .

[18]  R. Nigmatullin,et al.  Application of the generalized mean value function to the statistical detection of water in decane by near-infrared spectroscopy , 2005 .

[19]  Elena Luchinskaya,et al.  Stochastic and Chaotic Dynamics in the Lakes. , 2000 .