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We consider the separation of signals having a simplex constraint based on observations of noisy data using a fully Bayesian result. A joint density for the abundances (the simplex-constrained signal) is established. To specifically allow for the abundances to be sparse, this joint density is endowed with a parameter which is parameterized to encourage sparseness, unlike related previous work which...
Atmospheric profiles of temperature and water vapor mixing ratio can be estimated from hyperspectral measurement of radiation intensity from the atmosphere. Current estimation methods rely on iteration and linearization to invert the non-linear radiative transfer model which relates atmospheric profiles to radiation intensity. Model inversion and atmospheric profile estimation can be accomplished...
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