Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/1640
AuthorsCarniel, R. 
TitleNeural networks and dynamical system techniques for volcanic tremor analysis
Issue DateMar-1996
Series/Report no.39/2
URIhttp://hdl.handle.net/2122/1640
Keywordsneural networks
dynamical systems
time series analysis
volcanic tremor
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring 
AbstractA volcano can be seen as a dynamical system, the number of state variables being its dimension N. The state is usually confined on a manifold with a lower dimension f, manifold which is characteristic of a persistent «structural configuration». A change in this manifold may be a hint that something is happening to the dynamics of the volcano, possibly leading to a paroxysmal phase. In this work the original state space of the volcano dynamical system is substituted by a pseudo state space reconstructed by the method of time-delayed coordinates, with suitably chosen lag time and embedding dimension, from experimental time series of seismic activity, i.e. volcanic tremor recorded at Stromboli volcano. The monitoring is done by a neural network which first learns the dynamics of the persistent tremor and then tries to detect structural changes in its behaviour.
Appears in Collections:Annals of Geophysics

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