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This poster is devoted to measuring the basic characteristics of seismic signals in a situation where the seismogram is a complex superposition of several different types of waves and the responsible sources. The process whereby the characteristics are to be obtained can be considered as a mathematical problem in its own right. In contrast to the Fourier transform, the wavelet transform gives a two-dimensional representation of signals by separating them by frequency and time; these variables can be treated as independent. As a result, we are able to investigate the properties of a signal in the time domain and in the frequency domain. The processing algorithm we present here was developed for fast detection of a sudden change in the properties of a seismic process. It enables automatic identification of a change in the character of a seismic process during a time interval not in excess of four seconds. The algorithm is based on the wavelet transform. It should be emphasized that the algorithm is adaptive. We discuss the use of this algorithm to analyze records of the most recent large Japanese earthquake of March 2011. It is shown that the precursors of that earthquake are identified very reliably and automatically by this algorithm.