Issue |
EPL
Volume 102, Number 4, May 2013
|
|
---|---|---|
Article Number | 40003 | |
Number of page(s) | 6 | |
Section | General | |
DOI | https://doi.org/10.1209/0295-5075/102/40003 | |
Published online | 11 June 2013 |
Robust reconstruction of the Fokker-Planck equations from time series at different sampling rates
1 Department of Computer Science and Engineering, Shanghai Jiao Tong University - Shanghai, 200240, China
2 Shanghai Center for Systems Biomedicine and Department of Physics, Shanghai Jiao Tong University Shanghai 200240, China
(a) boyuan@sjtu.edu.cn (corresponding author)
Received: 18 March 2013
Accepted: 7 May 2013
The reconstruction of the Fokker-Planck equations from time series without prior information is still an open problem. Here, we propose a new method to robustly reconstruct different drift and diffusion terms at different sampling rates. Our method is based on the estimation of the transition probability densities for both of the time series and the stochastic differential equation. We approximate the two terms with the Chebyshev series. Without any prior information, our method can recover the orders and coefficients of the underlying polynomial drift and diffusion terms using the synthetic time series generated by four representative models at different sampling rates. The three important factors affecting the reconstructions are the optimal sample size, the orders, and the coefficients of the Chebyshev series, all of which can be totally determined by a given time series.
PACS: 05.45.Tp – Time series analysis / 89.75.-k – Complex systems / 05.40.-a – Fluctuation phenomena, random processes, noise, and Brownian motion
© EPLA, 2013
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.