article · 2010

Bayesian filtering with wavefunctions

Cited by 1Abstract and details only

Abstract

This paper describes a general framework for performing Bayesian filtering on probability density functions represented by the modulus squared of a wavefunction in an orthogonal function basis. The objective of this work is to find a sparse representation for high-dimensional non-Gaussian density functions enabling tractable implementations of the general Bayesian filtering problem. The general form of the Bayesian filtering algorithms employing the modulus squared of a wavefunction is presented without specification of a particular basis. A simple 0-th order implementation of this formulation for a bearing only sensor is also demonstrated.

Cite this paper

APA 7

McCalman, L., & Durrant‐Whyte, H. (2010). Bayesian filtering with wavefunctions. https://doi.org/10.1109/icif.2010.5711828

MLA 9

McCalman, Lachlan, and Hugh Durrant‐Whyte. “Bayesian filtering with wavefunctions.” 2010, pp. 1–7, https://doi.org/10.1109/icif.2010.5711828.

Chicago

McCalman, Lachlan, and Hugh Durrant‐Whyte. 2010. “Bayesian filtering with wavefunctions.” https://doi.org/10.1109/icif.2010.5711828.

Harvard

McCalman, L. and Durrant‐Whyte, H. (2010) ‘Bayesian filtering with wavefunctions’. Available at: https://doi.org/10.1109/icif.2010.5711828.

BibTeX

@article{mccalman2010bayesian,
  title = {{Bayesian filtering with wavefunctions}},
  author = {McCalman, Lachlan and Durrant‐Whyte, Hugh},
  pages = {1--7},
  year = {2010},
  doi = {10.1109/icif.2010.5711828}
}

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