Literature DB >> 20365695

1/f Noise from nonlinear stochastic differential equations.

J Ruseckas1, B Kaulakys.   

Abstract

We consider a class of nonlinear stochastic differential equations, giving the power-law behavior of the power spectral density in any desirably wide range of frequency. Such equations were obtained starting from the point process models of 1/fbeta noise. In this article the power-law behavior of spectrum is derived directly from the stochastic differential equations, without using the point process models. The analysis reveals that the power spectrum may be represented as a sum of the Lorentzian spectra. Such a derivation provides additional justification of equations, expands the class of equations generating 1/fbeta noise, and provides further insights into the origin of 1/fbeta noise.

Mesh:

Year:  2010        PMID: 20365695     DOI: 10.1103/PhysRevE.81.031105

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  3 in total

1.  Excitable human dynamics driven by extrinsic events in massive communities.

Authors:  Joachim Mathiesen; Luiza Angheluta; Peter T H Ahlgren; Mogens H Jensen
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-07       Impact factor: 11.205

2.  Specific Relationship between the Shape of the Readiness Potential, Subjective Decision Time, and Waiting Time Predicted by an Accumulator Model with Temporally Autocorrelated Input Noise.

Authors:  Aaron Schurger
Journal:  eNeuro       Date:  2018-02-12

3.  Emergent user behavior on Twitter modelled by a stochastic differential equation.

Authors:  Anders Mollgaard; Joachim Mathiesen
Journal:  PLoS One       Date:  2015-05-08       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.