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

Implementation of many statistical methods for large, multivariate data setsrequires one to solve a linear system that, depending on the method, is of thedimension of the number of observations or each individual data vector. This isoften the limiting factor in scaling the method with data size and complexity.In this paper we illustrate the use of Krylov subspace methods to address thisissue in a statistical solution to a source separation problem in cosmologywhere the data size is prohibitively large for direct solution of the requiredsystem. Two distinct approaches, adapted from techniques in the literature, aredescribed: one that uses the method of conjugate gradients directly to theKronecker-structured problem and another that reformulates the system as aSylvester matrix equation. We show that both approaches produce an accuratesolution within an acceptable computation time and with practical memoryrequirements for the data size that is currently available.

Fast solution of Sylvester-structured systems for spatial source separation of the Cosmic Microwave Background