Noise-induced bias in last principal component modeling of linear system
β Scribed by Jin Cao; Janos Gertler
- Book ID
- 104026714
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 335 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0959-1524
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Least squares provides consistent estimates of the regression coefficients pin the model E [ Y 1 x] = P x when fully accurate measurements of x are available. However, in biomedical studies one must frequently substitute unreliable measurements X in place of x. This induces bias in the least squares
This paper addresses least-squares estimation of parameters in digital input/output models of linear time-invariant distributed systems in the presence of white process and sensor noise. The systems of interest have state-space realizations in Hilbert spaces. Both "nite-dimensional and in"nite-dimen