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

This paper is concerned with the analysis and decomposition of medical multichannel data. We present a signal processing technique that reliably detects and separates signal components such as mMCG, fMCG, or MMG by involving the spatiotemporal morphology of the data provided by the multisensor geometry of the so-called multichannel superconducting quantum interference device (SQUID) system. The mathematical building blocks are coorbit theory, multi-ÃŽÂ±-modulation frames, and the concept of joint sparsity measures. Combining the ingredients, we end up with an iterative procedure (with component-dependent projection operations) that delivers the individual signal components

Coorbit Theory, Multi--Modulation Frames, and the Concept of Joint Sparsity for Medical Multichannel Data Analysis