Parameter-free resolution of the superposition of stochastic signals

Autor(en): Scholz, Teresa
Raischel, Frank
Lopes, Vitor V.
Lehle, Bernd
Waechter, Matthias
Peinke, Joachim
Lind, Pedro G.
Stichwörter: MARKOV PROPERTIES; Measurement noise; Observational noise; Physics; Physics, Multidisciplinary; Signal reconstruction; Signals superposition; Stochastic processes; SYSTEMS
Erscheinungsdatum: 2017
Herausgeber: ELSEVIER
Journal: PHYSICS LETTERS A
Volumen: 381
Ausgabe: 4
Startseite: 194
Seitenende: 206
Zusammenfassung: 
This paper presents a direct method to obtain the deterministic and stochastic contribution of the sum of two independent stochastic processes, one of Which is an Ornstein-Uhlenbeck process and the other a general (non-linear) Langevin process. The method is able to distinguish between the stochastic processes, retrieving their corresponding stochastic evolution equations. This framework is based on a recent approach for the analysis of multidimensional Langevin-type stochastic processes in the presence of strong measurement (or observational) noise, which is here extended to impose neither constraints nor parameters and extract all coefficients directly from the empirical data sets. Using synthetic data, it is shown that the method yields satisfactory results. (C) 2016 Elsevier B.V. All rights reserved.
ISSN: 03759601
DOI: 10.1016/j.physleta.2016.09.057

Show full item record

Google ScholarTM

Check

Altmetric