7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
https://doi.org/10.1142/s0219493705001262
Copy DOIJournal: Stochastics and Dynamics | Publication Date: Mar 1, 2005 |
Citations: 4 |
A nonlinear online Kalman type filter is proposed for the estimation of unknown function S(t) with the known smoothness β for the diffusion observed process with small, of the order ε2, diffusion coefficient. Assuming that the drift coefficient of the observed process depends on an unknown function S(t), we propose an approach to the analysis of this estimator based on the Lyapunov's functions method. The best possible rate of convergence of risks to 0, as ε → 0, is proven for β ≤ 2.
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.