One-cut-conditional-gradient

Authors: Giacomo Cristinelli, José A. Iglesias, Daniel Walter

This module solves the control problem with Total Variation regularization

$$\min_{u\in \text{BV}(\Omega)} \frac{1}{2\alpha} |Ku-y_d|^2 + \text{TV}(u,\Omega)$$

where K is an operator associated with a linear PDE.

It employs the method described in the paper "Linear convergence of a one-cut conditional gradient method for total variation regularization".

Important libraries:

FEniCS (Dolfin) --version 2019.1.0 (https://fenicsproject.org/)

NetworkX --version 3.0 (https://networkx.org)

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
SSN.py		SSN.py
insertion.py		insertion.py
main.py		main.py
mesh.py		mesh.py
plot.py		plot.py
setup.conf		setup.conf
utils.py		utils.py

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