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Relevance vector method in pattern recognition signals from seismic detection system


L. I. Dvoyris – Dr.Sci. (Eng.), Professor
P. V. Potapov

The task of pattern recognition is one of the most important in the field of artificial intelligence. To this day the solution for each application remains a difficult theoretical and technical problem. In the last decade an alternative method of support vector machine was also intensively developed, and received a similar name – Relevance Vector Machine, RVM. This article deals with the problem of binary classification, the difficulties in solving it, and show the different methods of classification based on relevant vector machines. There was a comparison of the methods based on the data of signal processing of seismic means of detection recorded during the field experiment. The results obtained by the authors suggest that the RVM method has the best accuracy and reliability performance of detection signals in the time domain, and a small number of relevant vectors can greatly simplify the hardware implementation of a subsystem based on the current detection method.

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