We study some numerical properties of a nonconvex variational problem which arises as the continuous limit of a discrete optimization method designed for the smoothing of images with preservation of discontinuities. The functional that has to be minimized fails to attain a minimum value. Instead, minimizing sequences develop gradient oscillations which allow them to reduce the value of the functional. The oscillations of the gradient exhibit analogies with microstructures in ordered materials. The pattern of the oscillations is analysed numerically by using discrete parametrized measures
Abstract. Averaging or gradient recovery techniques, which are a popular tool for improved convergen...
International audienceWe study pattern formation for a variational model displaying competition betw...
In recent years many researchers in material science have focused their attention on the study of co...
AbstractWe study some numerical properties of a nonconvex variational problem which arises as the co...
We study some properties of a nonconvex variational problem. We fail to attain the infimum of the fu...
Consiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7 Rome / CNR - Consiglio ...
We study numerically the pattern of the minimizing sequences of nonconvex problems which do not admi...
Discrete gradient methods are well-known methods of geometric numerical integration, which preserve ...
The goal of this paper is to describe the oscillatory microstructure that can emerge from minimizing...
We analyze a variational approach to image segmentation that is based on a strictly convex non-quadr...
This paper concerns an optimization algorithm for unconstrained nonconvex problems where the objecti...
We present a numerical bundle-type method for local minimization of a real function of several varia...
Abstract: "An implementation of the stochastic gradient minimization method is proposed as a viable ...
International audienceA recent trend in the signal/image processing literature is the optimization o...
A novel class of variational models with nonconvex q -norm-type regularizations ( 0<q<1 ) is conside...
Abstract. Averaging or gradient recovery techniques, which are a popular tool for improved convergen...
International audienceWe study pattern formation for a variational model displaying competition betw...
In recent years many researchers in material science have focused their attention on the study of co...
AbstractWe study some numerical properties of a nonconvex variational problem which arises as the co...
We study some properties of a nonconvex variational problem. We fail to attain the infimum of the fu...
Consiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7 Rome / CNR - Consiglio ...
We study numerically the pattern of the minimizing sequences of nonconvex problems which do not admi...
Discrete gradient methods are well-known methods of geometric numerical integration, which preserve ...
The goal of this paper is to describe the oscillatory microstructure that can emerge from minimizing...
We analyze a variational approach to image segmentation that is based on a strictly convex non-quadr...
This paper concerns an optimization algorithm for unconstrained nonconvex problems where the objecti...
We present a numerical bundle-type method for local minimization of a real function of several varia...
Abstract: "An implementation of the stochastic gradient minimization method is proposed as a viable ...
International audienceA recent trend in the signal/image processing literature is the optimization o...
A novel class of variational models with nonconvex q -norm-type regularizations ( 0<q<1 ) is conside...
Abstract. Averaging or gradient recovery techniques, which are a popular tool for improved convergen...
International audienceWe study pattern formation for a variational model displaying competition betw...
In recent years many researchers in material science have focused their attention on the study of co...