Rapid Joint Detection and Classification with Wavelet Bases via Bayes Theorem

Clear P-wave arrival of weak events and automatic onset determination using wavelet filter banks

“…That can be shown by the following equations: (10) Second stage approximation, A 2 , and detail, D 2 , can be determined in the same way as A 1 and D 1…”

“…Colak et al (2005) [7] and Kanwaldip and Dowla (1997) [8] used wavelet methods on three component stations while, Haijiang Zhang et al (2003) [9] used multi-scale wavelet analysis for singlecomponent recordings. Paul Gendron et al (2000) [10] built an algorithm based on wavelet coefficients for detection and classification performance on the New England Seismic Network (NESN) of Weston Observatory of Boston College. All these algorithms are either based on amplitude, envelope, or power of the seismic signal(s) in time or frequency domains.…”

“…Sophisticated adjustments of operational parameters to actual signals and seismic noise conditions at each seismic site had shown large error in practice making STA/LTA (short term average over long term average) the most popular choice [11]. STA/LTA algorithm is defined as the ratio between short term average and long term average of time series data however this algorithm also suffers from the same drawback that it requires setting some parameters [11]. In addition fast Fourier transform, FFT, analysis of non-stationary signals cannot describe the local transient features due to averaging over duration of the signal.…”

Implementation of Additional Seismological Software for the Determination of Earthquake Parameters Based on MatSeis and an Automatic Phase-detector Algorithm

“…The auto-and cross-correlation of two or three components may be used in order to identify various phase arrivals through polarization measurements (Magotra et al, 1987;Roberts et al 1989). Other techniques for automated detection of seismic phases include maximum likelihood (Christofferson et al, 1988;Ruud et al, 1988), fuzzy logic (Chu and Mendel, 1994), and wavelet transform (WT) (Anant and Dowla, 1997;Gendron et al, 2000). For automatic S-phase determination only a few algorithms have been developed (Wang and Teng, 1997;Cichowicz 1997).…”

Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals

“…More recently, in [5] continuous seismogram recordings have been represented by using the discrete wavelet transform and de-noising techniques and then classified into local, regional and teleseismic events categories.…”