Optimized spectral estimation for nonlinear synchronizing systems

Linda Sommerlade, Malenka Mader, Wolfgang Mader, Jens Timmer, Marco Thiel, Celso Grebogi, Björn Schelter

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In many fields of research nonlinear dynamical systems are investigated. When more than one process is measured, besides the distinct properties of the individual processes, their interactions are of interest. Often linear methods such as coherence are used for the analysis. The estimation of coherence can lead to false conclusions when applied without fulfilling several key assumptions. We introduce a data driven method to optimize the choice of the parameters for spectral estimation. Its applicability is demonstrated based on analytical calculations and exemplified in a simulation study. We complete our investigation with an application to nonlinear tremor signals in Parkinson's disease. In particular, we analyze electroencephalogram and electromyogram data.
Original languageEnglish
Article number032912
JournalPhysical Review. E, Statistical, Nonlinear and Soft Matter Physics
Volume89
Issue number3
DOIs
Publication statusPublished - 14 Mar 2014

Fingerprint

Spectral Estimation
nonlinear systems
Nonlinear Systems
electromyography
Parkinson disease
tremors
Parkinson's Disease
electroencephalography
Nonlinear Dynamical Systems
Data-driven
dynamical systems
Optimise
Simulation Study
Distinct
Interaction
simulation
interactions
False
Electroencephalogram

Cite this

Optimized spectral estimation for nonlinear synchronizing systems. / Sommerlade, Linda; Mader, Malenka; Mader, Wolfgang; Timmer, Jens; Thiel, Marco; Grebogi, Celso; Schelter, Björn.

In: Physical Review. E, Statistical, Nonlinear and Soft Matter Physics, Vol. 89, No. 3, 032912 , 14.03.2014.

Research output: Contribution to journalArticle

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AU - Schelter, Björn

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