Russian Journal of Earth Sciences Russian Journal of Earth Sciences Russian Journal of Earth Sciences 1681-1208 46898 ОРИГИНАЛЬНЫЕ СТАТЬИ ORIGINAL ARTICLES ОРИГИНАЛЬНЫЕ СТАТЬИ 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 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 Getmanov V G Getmanov V G Geophysical Center RAS, Moscow, Russia ru Geophysical Center RAS, Moscow, Russia ru 12 5 1 12 10 11 2021 https://rjes.ru/en/nauka/article/46898/view

The article deals with the problem of recognition of anomalies in time series with Raleigh- and 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.

The article deals with the problem of recognition of anomalies in time series with Raleigh- and 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.

Tsunami hydrostatic pressure sensors recognition anomalies Raleigh disturbances spectral-time analysis functions of frequency-time distribution decision-making procedures Tsunami hydrostatic pressure sensors recognition anomalies Raleigh disturbances spectral-time analysis functions of frequency-time distribution decision-making procedures

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