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Conference Papers Year : 2006

Joint segmentation of piecewise constant autoregressive processes by using a hierarchical model and a Bayesian sampling approach

Abstract

We propose a joint segmentation algorithm for piecewise constant AR processes recorded by several independent sensors. The algorithm is based on a hierarchical Bayesian model. Appropriate priors allow to introduce correlations between the change locations of the observed signals. Numerical problems inherent to Bayesian inference are solved by a Gibbs sampling strategy. The proposed joint segmentation methodology provides interesting results compared to a signal-by-signal segmentation.
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Dates and versions

inria-00119997 , version 1 (12-12-2006)

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Nicolas Dobigeon, Jean-Yves Tourneret, Manuel Davy. Joint segmentation of piecewise constant autoregressive processes by using a hierarchical model and a Bayesian sampling approach. IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP 2006), May 2006, Toulouse, France. ⟨10.1109/ICASSP.2006.1660575⟩. ⟨inria-00119997⟩
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