Seismic signal discrimination using adaptive system parameters

The motivation for the research presented is the idea of using seismic information to verify compliance with respect to a comprehensive test ban treaty. A method is given for automatically discriminating between seismic events by using a multilayer perceptron neural network system. The input to the neural net consists of the filter coefficients of an adaptive line enhancer. The seismic signals of concern in this research are those generated by earthquakes and underground nuclear explosions. The results presented indicate that a relatively simple neural net can successfully classify seismic events.<>