Tue, 06 Dec 2022 15:02:49 +0200
Oops, some μ were x in the README.
README.md | file | annotate | diff | comparison | revisions |
--- a/README.md Tue Dec 06 14:12:38 2022 +0200 +++ b/README.md Tue Dec 06 15:02:49 2022 +0200 @@ -5,11 +5,11 @@ point source localisation_” by Tuomo Valkonen ⟨tuomov@iki.fi⟩. It concerns solution of problems of the type $$ - \min_{μ ∈ ℳ(Ω)}~ F(x) + λ \|μ\|_{ℳ(Ω)} + δ_{≥ 0}(x), + \min_{μ ∈ ℳ(Ω)}~ F(μ) + λ \|μ\|_{ℳ(Ω)} + δ_{≥ 0}(μ), $$ where $F$ is a data term, and $ℳ(Ω)$ is the space of Radon measures on the -(rectangular) domain $Ω ⊂ ℝ^n$. Implemented are $F(x)=\frac12\|Ax-b\|_2^2$ and -$F(x)=\|Ax-b\|_1$ for the forward operator $A \in 𝕃(ℳ(Ω); ℝ^m)$ modelling a +(rectangular) domain $Ω ⊂ ℝ^n$. Implemented are $F(μ)=\frac12\|Aμ-b\|_2^2$ and +$F(μ)=\|Aμ-b\|_1$ for the forward operator $A \in 𝕃(ℳ(Ω); ℝ^m)$ modelling a simple sensor grid. For the 2-norm-squared data term implemented are the algorithms μFB, μFISTA, and μPDPS from the aforementioned manuscript along with comparison relaxed and fully corrective conditional gradient methods from the