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Multifractal Detrended Cross-Correlation Analysis of BVP model time series
by
Shang, Pengjian
, Xue, Chongfeng
, Jing, Wang
in
Autocorrelation
/ Automotive Engineering
/ Biological activity
/ Boundary value problems
/ Classical Mechanics
/ Control
/ Correlation analysis
/ Dynamical Systems
/ Engineering
/ Fractals
/ Mathematical analysis
/ Mathematical models
/ Mechanical Engineering
/ Nonlinearity
/ Original Paper
/ Oscillators
/ Time series
/ Topology
/ Vibration
2012
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Multifractal Detrended Cross-Correlation Analysis of BVP model time series
by
Shang, Pengjian
, Xue, Chongfeng
, Jing, Wang
in
Autocorrelation
/ Automotive Engineering
/ Biological activity
/ Boundary value problems
/ Classical Mechanics
/ Control
/ Correlation analysis
/ Dynamical Systems
/ Engineering
/ Fractals
/ Mathematical analysis
/ Mathematical models
/ Mechanical Engineering
/ Nonlinearity
/ Original Paper
/ Oscillators
/ Time series
/ Topology
/ Vibration
2012
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Multifractal Detrended Cross-Correlation Analysis of BVP model time series
by
Shang, Pengjian
, Xue, Chongfeng
, Jing, Wang
in
Autocorrelation
/ Automotive Engineering
/ Biological activity
/ Boundary value problems
/ Classical Mechanics
/ Control
/ Correlation analysis
/ Dynamical Systems
/ Engineering
/ Fractals
/ Mathematical analysis
/ Mathematical models
/ Mechanical Engineering
/ Nonlinearity
/ Original Paper
/ Oscillators
/ Time series
/ Topology
/ Vibration
2012
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Multifractal Detrended Cross-Correlation Analysis of BVP model time series
Journal Article
Multifractal Detrended Cross-Correlation Analysis of BVP model time series
2012
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Overview
The Bonhoeffer–van der Pol (BVP) oscillator has widely application in the modeling of biological processes, and it also has rich nonlinear behavior including different topological properties between the continuous-time BVP oscillator and the discrete one. Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) has proved useful in describing the correlations and detecting the scaling exponent of time series. We investigate the autocorrelations and cross-correlations of the time series in BVP model by using the MF-DCCA method. Our results show that there exist long range autocorrelations and cross-correlations in the BVP model time series, and that multifractal features are significant in the analyzed BVP model.
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