State Estimation in Distributed Parameter Systems via Least Squares and Invariant Embedding

Document Type

Article

Publication Date

6-1972

Abstract

Estimation of states in noisy dynamical systems is a problem whose solution is of significant importance in various scientific disciplines. Algorithms for filtering, smoothing and prediction estimates of lumped parameter system states have been derived by Kalman and Bucy [5], Bryson and Frazier [l], Cox [3], and Detchmendy and Sridhar [4]. The techniques utilized for generating these algorithms include orthogonal projection theory [5], maximum likelihood estimate [3], and the classical least squares error criterion combined with an invariant embedding technique [4].

Comments

The "Link to Full Text" button on this page loads the published article as it appeared in Journal of Mathematical Analysis and Applications, hosted at Elsevier's ScienceDirect portal.

©1972 by Academic Press, Inc. [Elsevier imprint].

This article is available under an Elsevier User License. Articles published under an Elsevier user license are protected by copyright. Users may access, download, copy, translate, text and data mine (but may not redistribute, display or adapt) the articles for non-commercial purposes provided that users:

  • Cite the article using an appropriate bibliographic citation (i.e. author(s), journal, article title, volume, issue, page numbers, DOI and the link to the definitive published version on ScienceDirect)
  • Maintain the integrity of the article
  • Retain copyright notices and links to these terms and conditions so it is clear to other users what can and cannot be done with the article
  • Ensure that, for any content in the article that is identified as belonging to a third party, any re-use complies with the copyright policies of that third party
  • Any translations, for which a prior translation agreement with Elsevier has not been established, must prominently display the statement: "This is an unofficial translation of an article that appeared in an Elsevier publication. Elsevier has not endorsed this translation."

DOI

10.1016/0022-247X(72)90070-4

Source Publication

Journal of Mathematical Analysis and Applications

Link to Full Text

Share

COinS