Linear dynamic filtering with noisy input and output
Markovsky, I. and De Moor, B., Soderstrom, T. (ed.) (2005) Linear dynamic filtering with noisy input and output. Automatica, 41, (1), 167-171.
Download
![[img]](http://eprints.soton.ac.uk/style/images/fileicons/application_pdf.png) |
PDF
- Accepted Version
Download (173Kb) |
|
PDF (Answer to the reviewers)
- Supplemental Material
Download (84Kb) |
Description/Abstract
Estimation problems for linear time-invariant systems with noisy input and output are considered. The smoothing problem is a least norm problem. An efficient algorithm using a Riccati-type recursion is derived. The equivalence between the optimal filter and an appropriately modified Kalman filter is established. The optimal estimate of the input signal is derived from the optimal state estimate. The result shows that the noisy input/output filtering problem is not fundamentally different from the classical Kalman filtering problem.
| Item Type: | Article |
|---|---|
| Related URLs: | |
| Keywords: | errors-in-variables model, Kalman filtering, optimal smoothing. |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 263299 |
| Date Deposited: | 06 Jan 2007 |
| Last Modified: | 05 Mar 2012 14:14 |
| Contributors: | Markovsky, I. (Author) De Moor, B. (Author) Soderstrom, T. (Editor) |
| Date: | 2005 |
| Status: | Published |
| Publisher: | Elsevier |
| Further Information: | Google Scholar |
| ISI Citation Count: | 10 |
| URI: | http://eprints.soton.ac.uk/id/eprint/263299 |
Actions (login required)
 |
View Item |
