Analysis of stochastic time series in the presence of strong measurement noise

Abstract

A new approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For the case of Gaussian distributed, exponentially correlated, measurement noise it is possible to extract the strength and the correlation time of the noise as well as polynomial approximations of the drift and diffusion functions from the underlying Langevin equation.

12 pages, 10 figures; corrected typos and references

References in corpus (2)

• On the proper reconstruction of complex dynamical systems spoilt by strong measurement noise
• Extracting strong measurement noise from stochastic series: applications to empirical data

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