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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A x = b (1.1) where A E RnX" is a large sparse real non-symmetric non-singular matrix and b E R" is a constant real vector is one of the major problems of numerical analysis. If the matrix is not too unstructured it may be possible to use direct methods but if the sparseness is of a random nature or if direct methods would lead to an unacceptable amount of fill-in then iterative methods are the only ones available. Since it is often impossible to guarantee convergence for the Jacobi, successive over-relaxation or similar methods attention has been focused on methods of conjugate-gradient (cg) type, despite the fact that the latter have

A Comparison of Three Basic Conjugate Direction Methods