Distributed Tikhonov regularization for ill-posed inverse problems from
a Bayesian perspective
Distributed Tikhonov regularization for ill-posed inverse problems from
a Bayesian perspective
We exploit the similarities between Tikhonov regularization and Bayesian hierarchical models to propose a regularization scheme that acts like a distributed Tikhonov regularization where the amount of regularization varies from component to component. In the standard formulation, Tikhonov regularization compensates for the inherent ill-conditioning of linear inverse problems by augmenting …