STRUCTURAL FUNCTIONS IN BINARY RANDOM PROCESS GENERATION BY PERMUTATION METHODS

Abstract

The PURPOSE of the paper is search for new and modernization of known methods for generating random processes with given static (probability distribution law) and dynamic (correlation and structure functions) probabilistic properties. METHODS. The main research methods are the methods of probability theory, mathematical statistics and numerical methods. RESULTS. The object of the study is a permutation technology for generating random processes with simultaneously set probability distribution law and autocorrelation function. This technology is simple in software implementation, has high speed and allows to enter required probability properties with the accuracy of their reflection sufficient for engineering application (for example, in simulation modeling). The Bernoulli (binary) law has been taken as a law of generated process probability distribution. The characteristics reflecting probabilistic dependencies in generated implementations of random processes have been considered. The structural functions of the binary process generated by a permutation procedure have been studied. CONCLUSION. The conducted research allowed to expand the possibilities of probabilistic dependency estimation due to the use of structural functions. This dependency estimation tool has broader indicative properties as it is able to identify random processes with stationary increments.