Abstract-In this study work we introduce a technically simple 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 approximations of solving statistics under various hypotheses. As an example of the mathematical expectation jumping of a random process, the appropriate detection algorithm is synthesized and the method of finding of the analytical expressions for the characteristics of its operating effectiveness is illustrated. Applying statistical computer modeling, we have found that the proposed method of the detection of the abrupt changes in parameters of fastfluctuating 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.

Scattering of optical waves by a multi-scale rough mirror surface as a phase screen is considered. To solve the problem we used the diffusion phase approximation and numerical model of a phase jump. The scattering intensity was averaged over the ensemble of realizations. The results of numerical calculations of the angular dependence of the intensity are presented for a backscattering demonstrating the effect of the roughness distribution over the scales and its secondary impact on the indicatrix of scattering for multiplicative surface modulation.

A new model of capacity planning problem applied to Virtual Desktop Infrastructure implementation is proposed. The possibility of applying the methods of integer mathematical programming to the problem of optimizing server set providing the predetermined number of virtual machines operating.

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