Seismic signals detection and classification using artiricial neural networks

Main Article Content

G. Romeo

Abstract

Pattern recognition belongs to a class of Problems which are easily solved by humans, but difficult for computers. It is sometimes difficult to formalize a problem which a human operator can casily understand by using examples. Neural networks are useful in solving this kind of problem. A neural network may, under certain conditions, simulate a well trained human operator in recognizing different types of earthquakes or in detecting the presence of a seismic event. It is then shown how a fully connected multi layer perceptron may perform a recognition task. It is shown how a self training auto associative neural network may detect an earthquake occurrence analysing the change in signal characteristics.

Article Details

How to Cite
1.
Romeo G. Seismic signals detection and classification using artiricial neural networks. Ann. Geophys. [Internet]. 1994Nov.25 [cited 2022Jul.7];37(3). Available from: https://www.annalsofgeophysics.eu/index.php/annals/article/view/4211
Section
OLD

Most read articles by the same author(s)