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Neural networks for blind-source separation of Stromboli explosion quakes.
Acernese, F; Ciaramella, A; De Martino, S; De Rosa, R; Falanga, M; Tagliaferri, R.
Afiliación
  • Acernese F; Dipt. di Sci. Fisiche, Universita di Napoli "Federico II", Italy.
IEEE Trans Neural Netw ; 14(1): 167-75, 2003.
Article en En | MEDLINE | ID: mdl-18237999
ABSTRACT
Independent component analysis (ICA) is used to analyze the seismic signals produced by explosions of the Stromboli volcano. It has been experimentally proved that it is possible to extract the most significant components from seismometer recorders. In particular, the signal, eventually thought as generated by the source, is corresponding to the higher power spectrum, isolated by our analysis. Furthermore, the amplitude of the source signals has been found by using a simple trick and so overcoming, for this specific case, the classical problem of ICA regarding the amplitude loss of the separated signals.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: IEEE Trans Neural Netw Asunto de la revista: INFORMATICA MEDICA Año: 2003 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: IEEE Trans Neural Netw Asunto de la revista: INFORMATICA MEDICA Año: 2003 Tipo del documento: Article País de afiliación: Italia