Regularization of linear least squares problems by total bounded variation
Regularization of linear least squares problems by total bounded variation
We consider the problem : (P) Minimize over u ∈ K ∩ X, where α≥ 0, β > 0, K is a closed convex subset of L2(Ω), and the last additive term denotes the BV-seminorm of u, T is a linear operator from L2 ∩ BV into the observation space Y. We formulate necessary optimality conditions for (P). Then we show that (P) 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...
Regularization of noncoercive constraints in Hencky plasticity
The aim of this paper is to find the largest lower semicontinuous minorant of the elastic-plastic energy of a body with fissures. The functional of energy considered is not coercive.
Relaxation of vectorial variational problems
Multidimensional vectorial non-quasiconvex variational problems are relaxed by means of a generalized-Young-functional technique. Selective first-order optimality conditions, having the form of an Euler-Weiestrass condition involving minors, are formulated in a special, rather a model case when the potential has a polyconvex quasiconvexification.
Resolvents and selections of accretive mappings in Banach spaces
Results for an optimal control problem with a semilinear state equation with constrained control
Robinson's implicit function theorem