Presentation 2007-12-19
Estimating phase equations from multivariate time series
Isao TOKUDA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) A novel approach is presented for extracting phase equations from multivariate time series data recorded from a network of weakly coupled limit cycle oscillators. Our aim is to estimate important properties of the phase equations including natural frequencies and interaction functions between the oscillators. Our approach requires the measurement of an experimental observable of the oscillators; in contrast to previous methods it does not require measurements in isolated single or two-oscillator setups. This non-invasive technique can be advantageous, for example, in biological systems, where extraction of few oscillators may be a difficult task. We apply this technique to simulated data from prototypical example of coupled limit cycle oscillators. It is shown that our technique enables precise estimation of the natural frequencies and the interaction function from only a single data set. The method is most efficient when data are taken from the non-synchronized regime where the phases of the oscillators are affected by coupling but where no complete phase locking of the oscillators occurs.
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Keyword(in English) coupled oscillators / phase reduction / interaction function / parameter estimation / time series analysis
Paper # NLP2007-108
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Conference Information
Committee NLP
Conference Date 2007/12/12(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Estimating phase equations from multivariate time series
Sub Title (in English)
Keyword(1) coupled oscillators
Keyword(2) phase reduction
Keyword(3) interaction function
Keyword(4) parameter estimation
Keyword(5) time series analysis
1st Author's Name Isao TOKUDA
1st Author's Affiliation School of Information Science, Japan Advanced Institute of Science and Technology()
Date 2007-12-19
Paper # NLP2007-108
Volume (vol) vol.107
Number (no) 399
Page pp.pp.-
#Pages 4
Date of Issue