Search signs changes in the state of the near-surface layer of the lithosphere based on the image analysis results reflecting the characteristics dynamics of the geoacoustic emission signal
Vestnik KRAUNC. Fiziko-matematičeskie nauki, Tome 47 (2024) no. 2, pp. 58-74

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The lithosphere physical state, including its surface layers, in a certain way characterizes the likelihood of the risk of catastrophic seismic events, indicates the degree of threat to human life and the risk of economic damage. One of the directions for assessing the lithosphere state is the analyzing result the characteristics variability of the geoacoustic emission signal at the observation point. The studies results carried out at the Institute of Cosmophysical Research and Radio Wave Propagation Far Eastern Branch of the Russian Academy of Sciences are presented. This make it possible to identify the dynamic characteristics of the geoacoustic emission signal associated with changes in the near-surface of the lithosphere. Recognition and assessment of the characteristics variability of geoacoustic emission signals on a given time scale of observations was carried out using a neural network approach. A methodology has been developed for classifying observed anomalies in the dynamics of geoacoustic emission signal characteristics
Keywords: lithosphere state, pattern recognition, of signal characteristics dynamics, neural networks.
Mots-clés : geoacoustic emission
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     author = {Yu.I. Senkevich},
     title = {Search signs changes in the state of the near-surface layer of the lithosphere based on the  image analysis results reflecting the characteristics dynamics of the geoacoustic emission  signal},
     journal = {Vestnik KRAUNC. Fiziko-matemati\v{c}eskie nauki},
     pages = {58--74},
     publisher = {mathdoc},
     volume = {47},
     number = {2},
     year = {2024},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VKAM_2024_47_2_a3/}
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Yu.I. Senkevich. Search signs changes in the state of the near-surface layer of the lithosphere based on the  image analysis results reflecting the characteristics dynamics of the geoacoustic emission  signal. Vestnik KRAUNC. Fiziko-matematičeskie nauki, Tome 47 (2024) no. 2, pp. 58-74. http://geodesic.mathdoc.fr/item/VKAM_2024_47_2_a3/