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

Distributed adaptive networks achieve better estimation performance byexploiting temporal and as well spatial diversity while consuming fewresources. Recent works have studied the single task distributed estimationproblem, in which the nodes estimate a single optimum parameter vectorcollaboratively. However, there are many important applications where themultiple vectors have to estimated simultaneously, in a collaborative manner.This paper presents multi-task diffusion strategies based on the AffineProjection Algorithm (APA), usage of APA makes the algorithm robust against thecorrelated input. The performance analysis of the proposed multi-task diffusionAPA algorithm is studied in mean and mean square sense. And also a modifiedmulti-task diffusion strategy is proposed that improves the performance interms of convergence rate and steady state EMSE as well. Simulations areconducted to verify the analytical results.

Diffusion Adaptation Over Clustered Multitask Networks Based on the Affine Projection Algorithm