English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we consider a class of nonconvex problems with linearconstraints appearing frequently in the area of image processing. We solve thisproblem by the penalty method and propose the iteratively reweightedalternating minimization algorithm. To speed up the algorithm, we also applythe continuation strategy to the penalty parameter. A convergence result isproved for the algorithm. Compared with the nonconvex ADMM, the proposedalgorithm enjoys both theoretical and computational advantages like weakerconvergence requirements and faster speed. Numerical results demonstrate theefficiency of the proposed algorithm.

Iteratively reweighted penalty alternating minimization methods with continuation for image deblurring