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3 results on '"Dobigeon, Nicolas"'

1. Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery

Author

Dobigeon, Nicolas, Tourneret, Jean-Yves, and Chein-I Chang

Subjects
Bayesian statistical decision theory -- Usage, Markov processes -- Analysis, Random noise theory -- Analysis, Signal processing -- Research, Digital signal processor, Business, Computers, Electronics, Electronics and electrical industries
Abstract

A hierarchical Bayesian model is presented for hyperspectral image unmixing. An extension of the algorithm is studied for mixtures with unknown numbers of spectral components belonging to a known library.

Published
2008

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

Author

Dobigeon, Nicolas, Tourneret, Jean-Yves, and Davy, Manuel

Subjects
Bayesian statistical decision theory -- Usage, Markov processes -- Analysis, Signal processing -- Methods, Monte Carlo method -- Usage, Digital signal processor, Business, Computers, Electronics, Electronics and electrical industries
Abstract

A joint segmentation algorithm is proposed for piecewise constant autoregressive (AR) processes recorded by several independent sensors. The results are illustrated by several simulations conducted with synthetic signals and real arc-tracking and speech signals.

Published
2007

3. Joint segmentation of multivariate astronomical time series: Bayesian sampling with a hierarchical model

Author

Dobigeon, Nicolas, Tourneret, Jean-Yves, and Scargle, Jeffrey D.

Subjects
Poisson distribution -- Analysis, Photons -- Research, Bayesian statistical decision theory, Business, Computers, Electronics, Electronics and electrical industries
Abstract

Bayesian sampling algorithms are studied for segmenting single and multiple time series by obeying Poisson distributions with piecewise constant parameters. A Gibbs sampling strategy has allowed joint estimation of the unknown parameters and hyperparameters and the results obtained from synthetic and real photon counting data have shown the performance of the proposed algorithm.

Published
2007

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