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Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications

Marco , Huber

Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications

Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications

Marco , Huber

Paperback | English
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Description

By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems.

Specifications

  • Publisher
    Karlsruher Institut für Technologie
  • Pub date
    Mar 2015
  • Pages
    304
  • Theme
    Probability and statistics
  • Dimensions
    210 x 148 x 19 mm
  • Weight
    443 gram
  • EAN
    9783731503385
  • Paperback
    Paperback
  • Language
    English

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