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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

It is of particular interest to reconstruct or estimate bandlimited graphsignals, which are smoothly varying signals defined over graphs, from partialnoisy measurements. However, choosing an optimal subset of nodes to sample isNP-hard. We formularize the problem as the experimental design of a linearregression model if we allow multiple measurements on a single node. Byrelaxing it to a convex optimization problem, we get the proportion of samplefor each node given the budget of total sample size. Then, we use aprobabilistic quantization to get the number of each node to be sampled.Moreover, we analyze how the sample size influences whether our object functionis well-defined by perturbation analysis. Finally, we demonstrate theperformance of the proposed approach through various numerical experiments.

Design of Sampling Set for Bandlimited Graph Signal Estimation