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

We present a new event trigger generator based on the Hilbert-Huangtransform, named EtaGen ($\eta$Gen). It decomposes a time-series data intoseveral adaptive modes without imposing a priori bases on the data. Theadaptive modes are used to find transients (excesses) in the background noises.A clustering algorithm is used to gather excesses corresponding to a singleevent and to reconstruct its waveform. The performance of EtaGen is evaluatedby how many injections in the LIGO simulated data are found. EtaGen is viableas an event trigger generator when compared directly with the performance ofOmicron, which is currently the best event trigger generator used in the LIGOScientific Collaboration and Virgo Collaboration.

Generating Event Triggers Based on Hilbert-Huang Transform and Its Application to Gravitational-Wave Data