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 introduces the use of Principal Component Analysis as a method todecompose the waveform catalogues to produce a set of orthonormal basisvectors. We apply this method to a set of supernova waveforms and compare thebasis vectors obtained with those obtained through Gram-Schmidt decomposition.We observe that, for the chosen set of waveforms, the performance of the twomethods are comparable for minimal match requirements up to 0.9, with 14Gram-Schmidt basis vectors and 12 principal components required for a minimalmatch of 0.9. This implies that there are many common features in the chosenwaveforms. Additionally, we observe the chosen waveforms have very similarfeatures and a minimal match of 0.7 can be obtained by decomposing only onethird of the entire set of waveforms in the chosen catalogue. We discuss theimplications of this observation and the advantages of eigen-decomposingwaveform catalogues with Principal Component Analysis.

Rotating stellar core-collapse waveform decompositon: a Principal Component Analysis approach