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

Constrained least squares problems arise in a variety of applications, andmany iterative methods are already available to compute their solutions. Thispaper proposes a new efficient approach to solve nonnegative linear leastsquares problems. The associated KKT conditions are leveraged to form anadaptively preconditioned linear system, which is then solved by a flexibleKrylov subspace method. The new method can be easily applied to imagereconstruction problems affected by both Gaussian and Poisson noise, where thecomponents of the solution represent nonnegative intensities. {Theoreticalinsight is given, and} numerical experiments and comparisons are displayed inorder to validate the new method, which delivers results of equal or betterquality than many state-of-the-art methods for nonnegative least squaressolvers, with a significant speedup.

Fast nonnegative least squares through flexible Krylov subspaces