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

The article deals with the problem of recognition of anomalies in time series with Raleighand tsunami-wave disturbances in signals from hydrostatic pressure sensors (HPS) of ocean bottom seismic stations in the framework of tsunami warning problem. The proposed method of spectral-time analysis (STAN) of signals from the sensors was based on computing the evaluations of functions of frequency-time distribution, decision-making procedures and non-linear filtering for the above problem. The developed STAN method was applied to recognize time intervals with Rayleigh and tsunami-wave disturbances in HPS signals. The proposed STAN method is quite universal and can be used to solve problems of recognition of anomalies in time series of geophysical data of different nature. This is the e-book version of the article, published in the Russian Journal of Earth Sciences (doi:10.2205/2012ES000522). It is generated from the original source file using LaTeX’s epub.cls class.

rossijskij žurnal nauk o zemle/russian journal of earth sciences

Method of spectral-time analysis for recognition of anomalies in time series with Raleigh- and tsunami-wave disturbances in signals from hydrostatic pressure sensors of ocean bottom seismic stations