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Linear Filtering Theory

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Part of the book series: Stochastic Modelling and Applied Probability ((SMAP,volume 13))

Abstract

The most valuable achievements to date of the filtering theory of Chapter 8 belong to the linear theory which forms the subject of the present chapter and which is associated with the names of Kalman and Bucy. The Kalman filter (as this theory has come to be known) has a central place in our discussion of linear filtering not merely because of the fact that it is the precursor of the general nonlinear theory treated in Chapter 8 (and is still its most important special case) but because of its extensive applications in the post-Sputnik era to problems of tracking of satellites, signal detection, stochastic control, and aerospace engineering.

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© 1980 Springer Science+Business Media New York

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Kallianpur, G. (1980). Linear Filtering Theory. In: Stochastic Filtering Theory. Stochastic Modelling and Applied Probability, vol 13. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-6592-2_10

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  • DOI: https://doi.org/10.1007/978-1-4757-6592-2_10

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-2810-8

  • Online ISBN: 978-1-4757-6592-2

  • eBook Packages: Springer Book Archive

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