Estimation of functions of a dependent variable
Regularization in state space
Regularization of linear least squares problems by total bounded variation
Regularization of linear least squares problems by total bounded variation
We consider the problem : Minimize over , where is a closed convex subset of (Ω), and the last additive term denotes the BV-seminorm of is a linear operator from ∩ into the observation space . We formulate necessary optimality conditions for (). Then we show that () admits, for given regularization parameters α and β, solutions which depend in a stable manner on the data z. Finally we study the asymptotic behavior when α = β → 0. The regularized solutions...
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