Studies of geoacoustic emission in a seismically active region in Kamchatka show that geoacoustic signals produce pronounced pulse anomalies during the earthquake preparation and post-seismic relaxation of the local stresses field at the observation point. The qualitative selection of such anomalies is complicated by a strong distortion and weakening of the signal amplitude. A review of existing acoustic emission analysis methods shows that most often researchers turn to the analysis of more accessible to study statistical properties and energy of signals. The distinctive features of the approach proposed by the authors are the extraction of informative features based on the analysis of time and frequency-time structures of geoacoustic signals and the description of various forms of recognizable pulses by a limited pattern set. This study opens up new ideas to develop methods for detecting anomalous behavior of geoacoustic signals, including anomalies before earthquakes. The paper describes a technique of information extraction from geoacoustic emission pulse streams of sound frequency range. A geoacoustic pulse mathematical model, reflecting the signal generation process from a variety of elementary sources, is presented. A solution to the problem of detection of geoacoustic signal informative features is presented by the means of description of signal fragments by the matrixes of local extrema amplitude ratios and of interval ratios between them. The result of applying the developed algorithm to describe automatically the structure of the detected pulses and to form a pattern set is shown. The patterns characterize the features of geoacoustic emission signals observed at IKIR FEB RAS field stations. A technique of reduction of the detected pulse set dimensions is presented. It allows us to find patterns similar in structure. A solution to the problem of processing of a large data flow by unifying pulses description and their systematization is proposed. A method to identify a geoacoustic emission pulse model using sparse approximation schemes is suggested. An algorithmic solution of the problem of reducing the computational complexity of the matching pursuit method is described. It is to include an iterative refinement algorithm for the solution at each step in the method. The results of the research allowed the authors to create a tool to investigate the dynamic properties of geoacoustic emission signal in order to develop earthquake prediction detectors.

A new system approach to the identification and systematization of geophysical pulses is described. It includes stages of detection, analysis, object and structural description, pulse classification. In order to identify the pulses in geoacoustic emission, we apply a method based on the calculation of adaptive threshold, the values of which are estimated by the results of signal root-mean-square deviation in a moving window of a defined size. The detected pulses are described and identified by an adaptive matching pursuit algorithm which allows us to decompose the pulse into linear combination of basic functions from a combined Gauss-Berlage dictionary with minimum spatial and time costs and with the required accuracy of constructed approximations. Within the framework of object approach, pulses are described by a combination of features such as the number of functions in a decomposition, function type, parameters etc. We present a method of reduction of innumerable diversity of identified pulses to a denumerable set of patterns. It is based on structural transformation of geoacoustic emission pulses with simultaneous automatic procedure of classification. The results obtained during the application of the described system approach to the analysis of geoacoustic signals are summarized in a Geophysical Signal Catalogue.

The results of the study of the possibility of using the empirical mode decomposition method for cleaning geoacoustic emission signals from various types of noise are presented. It is shown that the application of the method allows to increase the ratio of the signal noise 3-6 dB depending on the ratio of signal dispersion and noise in the input signal. The examples demonstrate the ability to remove trends and harmonic interference, as well as the ability to highlight a useful signal when masking its powerful noise. A comparative evaluation of the method in relation to the low-frequency filtration is carried out. The limitation of the method applicability in the case of processing of pulse signals asymmetric with respect to its average value is indicated.

Abstract. The example of linguistic processing of acoustic signals of a seismic event would be an information approach to the processing of non-stationary signals. The method for converting an acoustic signal into an information message is described by identifying repetitive self-similar patterns. The definitions of the event selection indicators in the symbolic recording of the acoustic signal are given. The results of processing an acoustic signal by a computer program realizing the processing of linguistic data are shown. Advantages and disadvantages of using software algorithms are indicated.

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