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On nonlinear least-squares filtering

โœ Scribed by J.B. Pearson

Publisher
Elsevier Science
Year
1967
Tongue
English
Weight
427 KB
Volume
4
Category
Article
ISSN
0005-1098

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โœฆ Synopsis

This paper considers the problem of sequential estimation of the state of a nonlinear process from noisy measurement data. In a previous paper [1] the problem was concerned with measurements which are linear combinations of the state variables. In this paper a different approach to the problem is used which results in filter equations for processes whose measurements are nonlinear combinations of the process state.

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Currently available software for nonlinear regression does not account for errors in both the independent and the dependent variables. In pharmacodynamics, measurement errors are involved in the drug concentrations as well as in the eects. Instead of minimizing the sum of squared vertical errors (OL