Sparsity Based Methods for Overparameterized Variational Problems

Sparsity Based Methods for Overparameterized Variational Problems

Abstract—Two complementary approaches have been extensively used in signal and image processing leading to novel results, the sparse representation methodology and the variational strategy. Recently, a new sparsity based model has been proposed, the cosparse analysis framework, which may potentially help in bridging sparse approximation based methods to the traditional total-variation minimizat...

Sparsity Based Methods for Overparametrized Variational Problems

Two complementary approaches have been extensively used in signal and image processing leading to novel results, the sparse representation methodology and the variational strategy. Recently, a new sparsity based model has been proposed, the cosparse analysis framework, that has established a very interesting connection between the two, highlighting shown how the traditional total variation mini...

A Survey of Direct Methods for Solving Variational Problems

This study presents a comparative survey of direct methods for solving Variational Problems. Thisproblems can be used to solve various differential equations in physics and chemistry like RateEquation for a chemical reaction. There are procedures that any type of a differential equation isconvertible to a variational problem. Therefore finding the solution of a differential equation isequivalen...

Iterative Methods for Equilibrium Problems, Variational Inequalities and Fixed Points

iterative methods for equilibrium problems, variational inequalities and fixed points