Seismic signal detection by fractal dimension analysis

We introduce a new detection algorithm with improved local and regional sei smic signal recognition. The method is based on the difference between seis mic signals and background random noise in terms of fractal dimension D. We compare the new method extensively with standard methods currently in use at the Seismic Network of the Istituto Nazionale di Geofisica. Results from the comparisons show that the new method recognizes seismic phases detecte d by existing procedures, and in addition, it features a greater sensitivit y to smaller signals, without an increase in the number of false alarms. Th e new method was tested on real continuous data and artificially simulated high-noise conditions and demonstrated a capability to recognize seismic si gnals in the presence of high noise. The efficiency of the method is due to a radically different approach to the topic, in that the assertion that a signal is fractal implies a relationship between the spectral amplitude of different frequencies. This relationship allows, for the fractal detector, a complete analysis of the entire frequency range under consideration.