Estimation of the input parameters in the Ornstein-Uhlenbeck neuronal model
✍ Scribed by Ditlevsen, Susanne; Lansky, Petr
- Book ID
- 120154444
- Publisher
- The American Physical Society
- Year
- 2005
- Tongue
- English
- Weight
- 121 KB
- Volume
- 71
- Category
- Article
- ISSN
- 1063-651X
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
## Abstract This paper deals with optimal designs for Gaussian random fields with constant trend and exponential correlation structure, widely known as the Ornstein–Uhlenbeck process. Assuming the maximum likelihood approach, we study the optimal design problem for the estimation of the trend µ and
A large deviation principle (LDP) with an explicit rate function is proved for the parametric estimation of the Omstein-Uhlenbeck process. We establish a LDP for the quadratic variation of the diffusion process and for the score function by applying the method of parameter-dependent change of measur