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 study the convergence of Alternating Projection (AP)algorithm for the matrix completion and compressed sensing problems. We alsopresent computational evidence for the excellent performance of the algorithm.Also, in the last section, we prove using algebraic-geometric techniques that,fixing the known positions, if a rank r matrix can be completed in finitelymany ways using one given set of known entries, then, for almost all set ofknown entries, the matrix can be only completed into a rank r matrix infinitely many ways.

On Convergence of the Alternating Projection Method for Matrix Completion and Sparse Recovery Problems