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In this study work we introduce a technically sim- ple way of the detection of an abrupt change in parameters of fast fluctuating Gaussian processes in the conditions of parametric prior uncertainty. For this purpose, we suggest new approxima- tions of solving statistics under various hypotheses. As an exam- ple of the mathematical expectation jumping of a random process, the appropriate detection algorithm is synthesized and the me- thod of finding of the analytical expressions for the characteris- tics of its operating effectiveness is illustrated. Applying statistic- al computer modeling, we have found that the proposed method of the detection of the abrupt changes in parameters of fast- fluctuating random processes is operable, and the theoretical formulas for the detection characteristics well conform with the corresponding experimental data in a wide range of parameter values of the analyzed process.

The New Approach to the Detection of the Abrupt Change of Fast Fluctuating Random Processes in the Conditions of Parametric Prior Uncertainty