In certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate in the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Assuming that the infinite observation history is available, the paper establishes the lower steady-state estimation bound for any noncausal estimator applied to a linear system with randomly drifting coefficients (under Gaussian assumptions). This lower bound complements the currently available one, which is restricted to causal estimators.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1016/j.automatica.2007.05.020
- Category
- Publikacja w czasopiśmie
- Type
- artykuł w czasopiśmie z listy filadelfijskiej
- Language
- angielski
- Publication year
- 2008