Adaptive classification method and measurement of intermittent random process characteristics

Results are presented of an analytic construction and investigation of adaptive data classification algorithms for intermittent turbulence. A decision making rule is presented, relationships are derived to estimate the classification accuracy. A three-level procedure is described for processing the intermittency, including the calculation algorithms for the initial point, self-teaching, and optimal classification. It is shown that the method proposed permits realization of total automation of intermittency data processing.Translated from Teoreticheskaya i Prikladnaya Mekhanika, No. 18, pp. 119–123, 1987.