Relation To Probabilistic Formulation
The probabilistic formulation of an inverse problem introduces (when all uncertainties are Gaussian) a covariance matrix representing the a priori uncertainties on the model parameters, and a covariance matrix representing the uncertainties on the observed parameters (see, for instance, Tarantola, 2004 ). In the special case when these two matrices are diagonal and isotropic, and, and, in this case, the equations of inverse theory reduce to the equations above, with .
Read more about this topic: Tikhonov Regularization
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