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Understanding the Kalman filter: an object oriented programming perspective

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journal contribution
posted on 2017-06-07, 00:22 authored by Snyder, Ralph D., Forbes, Catherine S.
The basic ideas underlying the Kalman filter are outlined in this paper without direct recourse to the complex formulae normally associated with this method. The novel feature of the paper is its reliance on a new algebraic system based on the first two moments of the multivariate normal distribution. The resulting framework lends itself to an object-oriented implementation on computing machines and so many of the ideas are presented in these terms. The paper provides yet another perspective of Kalman filtering, one that many should find relatively easy to understand.

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Year of first publication

1999

Series

Department of Econometrics and Business Statistics

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