Neural Networks for Blind-Source Separation of Stromboli Explosion Quakes  

Oleh:

Acernese, Fausto ; Martino, S. De ; Ciaramella, A. ; Rosa, R. De ; Falanga, M. ; Tagliaferri, R.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 14 no. 1 (Jan. 2003), page 167-175.
Topik: Relief explosion; seismic data analysis; ICA; non linear systems; independent component analysis; blind - source separation; data analysis

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.8 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

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.

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