An efficient particle filtering technique on the Grassmann manifold

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Subspace tracking methods are widespread in signal and image processing. To reduce the inﬂuence of perturbations or outliers on the measurements, some authors have used a stochastic piecewise constant velocity model on the Grassmann manifold. This paper presents an efﬁcient way to simulate such a model using a particular representation of the Grassmann manifold. By doing so, we can reduce the spatial and time complexity of ﬁltering techniques based on this model. We also propose an approximation of this system which can be computed in a ﬁnite number of operations and show similar results if the subspace variation is slow.

Quentin Rentmeesters, Pierre-Antoine Absil, Paul V

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Constant Velocity Model | Grassmann Manifold | ICASSP 2010 | Signal Processing | Subspace Tracking Methods |

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Added	06 Dec 2010
Updated	06 Dec 2010
Type	Conference
Year	2010
Where	ICASSP
Authors	Quentin Rentmeesters, Pierre-Antoine Absil, Paul Van Dooren, Kyle Gallivan, Anuj Srivastava

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An efficient particle filtering technique on the Grassmann manifold

Constant Velocity Model | Grassmann Manifold | ICASSP 2010 | Signal Processing | Subspace Tracking Methods |

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